Media and drive validation in tape libraries

ABSTRACT

A method for validating media and drives. The method includes receiving a validation request for a data storage tape in a library and, with the tape loaded into a predefined gold drive in the tape library, performing a statistical analysis on the tape to determine an operating parameter such as a measure of read margin for the tape in the predefined gold drive. The method includes validating the tape when the operating parameter compares favorably with a threshold limit defined for the operating parameter for the tape library. The method includes, when the operating parameter fails to compare well with the threshold limit, running a performance test on a drive qualified tape from the library loaded into the predefined gold drive and, when the drive qualified tape passes the test, identifying the tape as degraded. The method includes, when the drive qualified tape fails the test, re-qualifying the gold drive.

BACKGROUND

1. Field of the Description

The present description relates to magnetic tape data storage and, inparticular, to methods and systems for monitoring operation of atape-based data storage system including gathering data from tapelibraries and including validating media (e.g., data storage tapes) andtape drives with regard to their ongoing operational quality oroperating parameters.

2. Relevant Background

For decades, magnetic tape data storage has offered cost and storagedensity advantages over many other data storage technologies includingdisk storage. A typical small to large-sized data center will deployboth tape and disk storage to complement each other, with the tapestorage often being used for backup and archival data storage. Due tothe increased need for securely storing data for long periods of timeand due to the low cost of tape, it is likely that tape-based datastorage will continue to be utilized and its use will only expand forthe foreseeable future.

Briefly, magnetic tape data storage uses digital recording on tomagnetic tape to store digital information, and the tape is packaged incartridges and cassettes (i.e., the storage media or simply “media”).The device that performs writing and reading of data is a tape drive,and mainframe-class tape drives are often installed within robotic tapelibraries that may be quite large and hold thousands of cartridges toprovide a tremendous amount of data storage (e.g., each tape may holdseveral terabytes of uncompressed data).

An ongoing challenge, though, for the data storage industry is how tomanage and monitor data centers, and, particularly, how to bettermonitor tape storage media and devices. For example, customers demandthat data be safely stored with lower tape administration costs. In thisregard, the customers desire solutions that efficiently and proactivelymanage data center tape operations including solutions that providefailure analysis for problematic or suspect media and drives. Further,customers demand data collection regarding operations to benon-invasive, and the management solution should provide recommendedcorrective actions. Data storage customers also want their investment intape technologies to be preserved and data integrity maintained. Thismay involve monitoring tape capacities in volumes and/or libraries,flagging media to be migrated, and advising on resource rebalancing.Customers also desire a management solution that provides an effectiveand useful user interface to the collected tape operations data andreporting of detected problems or issues.

Unfortunately, existing tape data storage management solutions andsystems have not met all of these needs or even fully addressed customerdissatisfiers. For example, existing management tools typically onlycollect and report historical data, and it can be very difficult afterthe fact or after a problem with tape operations occurs to determinewhether a particular drive or piece of media was the cause of a failure.This can lead to cartridges or other media being needlessly replaced ora tape drive being removed for repair or even replaced withoutverification of which component caused a fault. Some systems managemedia lifecycles, but this typically only involves tracking the age oroverall use of media to provide warnings when a tape or other media ispotentially nearing the end of its useful life to allow a customer toremove the media. Existing systems also often only provide alerts aftera failure or problem has occurred, e.g., alert when already in a crisismode of operation. Further, reporting is limited to predefined reportsthat make assumptions regarding what information likely will beimportant to a customer and provide the customer with no or littleability to design a report or select data provided to them by the tapeoperations management system.

There remains a need for improved systems and methods (e.g., softwareproducts) for providing customers with information to efficiently andtimely manage data center tape operations. Preferably, the informationwould include tape analytics that would allow proactive management ofthe tape operations including validation of tapes (“media”) and driveswithin all of the tape libraries within a data center or used by one ormore clients.

SUMMARY

To address the above and other issues, a method and system is providedfor monitoring and analyzing operations of a tape infrastructure as maybe found in a data center performing tape-based data storage. Forexample, a data storage system may include a server or appliance runninga storage tape analytics (STA) application or software suite/tool thatimplements a data warehouse approach to monitoring a tapeinfrastructure. The STA application receives or gathers raw data from anumber of data sources that may include a library management applicationand one, two, or more tape libraries, with the library data beingtransmitted using a data transport mechanism such as via SNMP (SimpleNetwork Management Protocol). The raw data may include data pertainingto operations of the library as well as its components including tapedrives and tape media (or cartridges) such as mount records, I/O orother records indicating what occurred while media was mounted in adrive, and dismount records. The data is not tied to a single library ordrive but will, instead, include data on multiple libraries (whenapplicable) and numerous drives and media (which may be of differingtypes and/or may be fabricated by differing manufacturers).

The STA application applies the warehouse approach by utilizing an STAdatabase to stage or store the received data records in staging tables,to clean up or transform the data into useful standardized or normalizedform(s), and to summarize the collected operations data. The STAapplication includes a user interface module for providing a user withan interface (e.g., a browser-based graphical user interface (GUI)), andthe STA application makes no or few assumptions about which data will bepertinent to the user. Instead, the user is able to interact with thetape operations data in the STA database via the GUI to view and processall of the gathered data, which may include historical data as well ascurrent operating data to facilitate trending-type analyses. The user isable to customize views and screens in the GUI, and these customizedviews and screens may be saved for later use by that user or for sharingwith other monitoring personnel.

The STA application includes an analytics subsystem that may perform thesummarization and also may perform algorithms and computations on theraw and summarized data to determine the current health of variouscomponents of the tape infrastructure. For example, drive healthindicators may be provided for all the drives in each library of a datacenter in a view of the GUI. An alerting module of the STA applicationmay provide alerts to one or more recipients based on monitoredoperating conditions such as when an operating parameter of a tapelibrary crosses a predefined (user-defined) threshold. The alerts mayalso be provided in views in the GUI and stored in the STA database forlater viewing or processing. Further, the STA analytics subsystem mayuse algorithms and computations to determine or predict when a componentof the tape infrastructure may have operational problems (or reducedhealth).

Still further, and of most relevance or significance to the methods andsystems described herein and then claimed in the attached claims, theSTA analytics subsystem preferably includes a media and drive validation(MDV) module that functions to perform validation processes on bothmedia (tapes) and tape drives found in one or more tape libraries of adata center(s).

More particularly, a method is provided for validating tape drives andmedia in a tape library. The method includes, with a computer running ananalytics module (e.g., with an MDV module/program), receiving avalidation request for a tape in the tape library. The method furtherincludes, with the tape loaded into a predefined gold drive in the tapelibrary, performing a statistical analysis on the tape to determine anoperating parameter for the tape in the predefined gold drive. Then, themethod includes, with the analytics module, validating the tape when theoperating parameter is greater than a threshold limit defined for theoperating parameter for media in the tape library.

In some embodiments of the method, the operating parameter is readquality index (RQI), and the threshold limit may then be an RQI of 40 to70 percent (such as 50 percent). The method may further include, whenthe operating parameter is less than about the threshold limit, runninga performance test on a drive qualified tape from the library loadedinto the predefined gold drive and, when the drive qualified tape passesthe performance test, identifying the tape as having degradedperformance (e.g., degraded read margin). The method may also include,when the drive qualified tape fails the performance test, re-qualifyingthe predefined gold drive.

Re-qualifying or re-certifying as golden may include determiningwhether, after cleaning of the predefined gold drive, the drivequalified tape and a predefined gold tape from the tape library pass aperformance test when loaded into the predefined gold drive. In somecases, the method also includes, when both the drive qualified tape andthe predefined gold tape pass the performance test, identifying the tapeas having degraded performance. The method may also include, when thedrive qualified tape fails the performance test and the predefined goldtape passes the performance test, identifying the tape as havingdegraded performance. In some embodiments, the operating parameter isRQI and the predefined gold tape has an RQI greater than about 75percent. During performance of the validating method the predefined goldtape, the drive qualified tape, and the predefined gold drive areconcurrently available for data operations in the tape library and foruse by the analytics module. Further, the data used in initializingsteps and in validating is the customer's data (e.g., the data stored onthe tapes of the library during normal operations of the library and notsome predefined unique set of test data).

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a functional block or schematic illustration of a data storagesystem implementing a storage tape analytics (STA) tool of the presentdescription to monitor and analyze operations of tape-based data storagein the system;

FIG. 2 provides a diagram of key software components or technologiesthat may be provided in an implementation of a STA product or an STAapplication provided on an appliance or installed on a customer's/user'sserver;

FIG. 3 is a functional block diagram of the architecture of an exemplarydata storage system implementing the storage tape analytics of thepresent description;

FIG. 4 is functional block diagram providing an implementation view ofan STA architecture with further detail on components or features of thedata adapters subsystem, the analytics subsystem, and the alertsubsystem of the STA application of FIG. 3;

FIG. 5 illustrates an entity-relationship diagram (ERD) of tape systemmodel tables for one exemplary, but not limiting, implementation of anSTA application and STA database;

FIG. 6 illustrates a schema for tracking exchanges in the STA database;

FIG. 7 illustrates a schema that may be used in the STA database tocollect data on robotic moves in tape libraries;

FIG. 8 illustrates a schema that may be used in the STA database togather and store computed analytics or computed facts/results ofanalyses;

FIG. 9 illustrates a schema that may be used in the STA database togather data for drives and media that is summarized over time by the STAapplication;

FIG. 10 illustrates a schematic or functional block diagram of a portionof data storage system implementing a data adapter to receive andretrieve data from a data source and provide this data in a raw ortransformed form to tables in an STA database;

FIG. 11 illustrates a schematic diagram of a portion of a data storagesystem implementing a data analytics subsystem to perform analyses ofraw tape operations data and to perform summarizations, with the outputsof the analytics and summarizer being viewable in a GUI and used togenerate alerts;

FIG. 12 illustrates a functional block or schematic illustration of aportion of a data storage system implementing an STA application toprovide alerts via the STA alert subsystem;

FIGS. 13-16 illustrate screen shots of an embodiment of a graphical userinterface (GUI) generated by the STA application to display datagathered and computed by the STA application to a user of the STAsystem;

FIG. 17 provides a flow chart of a tape operations monitoring andanalysis method that may be performed during operations of a datastorage system described herein that includes and uses an STAapplication such as the STA applications shown in FIGS. 1-4 or the like;

FIG. 18 provides a flow diagram of a health monitoring and predictingmethod as may be carried out with an STA application and an includedanalytics module as described herein;

FIG. 19 provides three graphs providing representations of the use ofread margin measurements in performance of validation or verification ofoperation of drives and tapes by a MDV module or as part of a MDVmethod;

FIG. 20 provides a flow chart or diagram of a method of initializing asite or library for media and drive validation with an MDV module of thepresent description;

FIG. 21 shows a flow diagram or block diagram of a method of using orperformed by the MDV module and its functions to test or validate atarget tape or media in a customer library;

FIG. 22 shows a flow diagram or block diagram of a method of using orperformed by the MDV module upon failure of target tape (e.g., failureof tape in the method of FIG. 21); and

FIG. 23 shows a flow diagram or block diagram of a method of using orthat is performed by the MDV module upon failure of the gold/DQ drive.

DETAILED DESCRIPTION

Briefly, a tape analytics system and method is described that is builtup around a storage tape analytics (STA) software suite, application, orproduct that may be run or executed upon a customer's (or tape operationmonitor's) computer system such as on a server that is communicativelylinked with a tape-based data storage system or data center (e.g.,automated tape libraries, tape drives, and tape media). The STAapplication is an integrated management solution for the tapeinfrastructure of the data center that functions to capture data aboutthe tape infrastructure, and this data is warehoused in a database thatcan be accessed in user-defined or default interfaces, alerts, andreports. The data gathered may include data about tape mounts,dismounts, I/O that occurs while tapes are mounted, errors during I/O orrobotic processes, and the status of all the tape infrastructurecomponents.

The STA application provides a customer or other monitor of a tapeinfrastructure with tape business insight to efficiently and proactivelymanage data center tape operations. As will become clear from thefollowing description, the STA application can provide a user a numberof advantages. For example, lower tape total cost of ownership (TCO) maybe achieved via increased tape system reliability and a singlepane-of-glass for monitoring tape operations (e.g., a graphical userinterface (GUI) provided by the STA application on a client device). TheSTA application also provides simplified tape management through thefollowing: (1) proactive tape media and drive health management; (2)customizable alerts and reporting; (3) functions and features supportingnovice and expert users; and (4) analytics to help customers/managersmake decisions about the tape hardware and media in their managedenvironment or data center. Increased tape performance may be achievedas the STA application provides a database of library movements, toolsto optimize existing hardware, and insights into drive balancingsolutions. The STA application presents a scalable and flexible tapemanagement solution as it may support monitoring of thousands of drivesand even larger numbers of tape media while typically also beinginteroperable with existing and future hardware. The STA application maybe deployed with a simple deployment model such as standalone software.

Prior to turning to an exemplary data storage system utilizing an STAapplication, it may be useful to further explain how an STA applicationmay address some of the main problems and reasons of dissatisfaction ofdata center or tape storage managers or customers. It is desirable tokeep data safe and to lower tape administration costs. In this regard,the STA application provides a comprehensive set of analytics to predictdrive and media failures. Failure analysis is also provided forproblematic or suspect media and drives as well as generatingrecommended corrective actions. In addition to such predictive analysis,the set of analytics may include a media and drive validation (MDV)module that acts to provide validation of drives and also media withinone or more tape libraries in a unique and non-intrusive mannerdescribed beginning with FIG. 19. The STA application further mayprovide alerts and workflow management for critical situations. Datacollection is non-invasive with the STA application providing alow-touch approach for the analysis of tape operations. In some cases,the STA application provides integration with leading edge tapecapabilities with DADP.

Tape operation managers also wish to preserve their investment in tapetechnologies. With this in mind, the STA application monitors tapecapacity of current volumes and also predicts capacity for futuregrowth. The STA application may also flag media to be migrated andadvise on resource rebalancing according to identified usage patterns.Tape capacity may be mapped to public tape technology roadmaps and toplanned tape generational migrations. Further, the STA application maymonitor tape partition usage and support various business metrics thatcan be defined by the customer.

Significantly, the STA application also provides a “single pane ofglass” for tape intelligence. Specifically, the STA application canprovide a single UI for statistics across tape libraries, tape media,tape drives, and host applications. It can also correlate data thatpreviously would have to have been accessed (if available at all)through separate applications. The STA application provides a flexiblesystemic view instead of silo-only statistical views. The STAapplication also can provide predefined, custom, and what-if queriesacross data sets for enhanced tape analytics. Management is provided atscale and across a hybrid set of tape solutions including logicalgroupings (which may be defined or set by the customer or user of theSTA application).

The STA application is a scalable solution to tape analytics andmanagement that is able to grow in both physical scope and in terms oftypes and numbers of devices that can be monitored. Its open andextensible architecture permits the inclusion of increased functionalityin a seamless, non-disruptive manner. Support for new hardware types andfacilities may be easily added to the STA application. The STAapplication exposes a rich graphical interface via a web browser, forexample, to act as the interface between a user and the server uponwhich the STA application is provided or running.

The STA application will typically not require explicit installation butwill, instead, be provided via a web interface displayed on the client'sworkstation. The STA application may use industry standard technologiessuch the JAVA™ technology so that it is feature-full and robust and canbe used on a variety of different end-user workstations and personalcomputers with no (or little) further installation requirements. In someembodiments, the STA application will generally be delivered as either asoftware product that customers/users may install onto an existingserver (e.g., a Solaris server, a Linux server, or a server with anotheroperating system) or as part of an appliance where all necessarycomponents are pre-installed on the appliance, which is thencommunicatively linked to the monitored tape infrastructure as part ofits installation at the customer's/user's site.

Turning now to the figures, FIG. 1 illustrates a data storage system 100that may implement the monitoring and analytics described herein toprovide enhanced management of a tape infrastructure. In this regard,the system 100 includes a number of tape libraries 110, 114, 118 eachwith a number of tape drives 112, 116, 119. Tape media (e.g.,cartridges) is automatically mounted and dismounted from these drives112, 116, 119 although particular media is not shown in FIG. 1 suchmedia will be inserted into these drives and monitored by the STAapplication 164 including its MDV module. Exemplary libraries and drivesare shown in FIG. 1, but the system 100 may be implemented with nearlyany type of library, drives, and tape media (e.g., not limited to thoseof a particular manufacturer in the data storage industry). Duringoperation of the data storage system 100, library, media, and drive data120 is transported via a data transport mechanism (e.g., SNMP, anEthernet port, SCSI, or the like) over an IP network (e.g., a local areanetwork (LAN) or the like) to an STA server 160. For example, the data120 may include mount records, records of what occurred while a tapemedia was in a drive, and a dismount record and data specificallydiscussed below as being used and processed by the MDV module of the STAapplication 164. Also, it should be noted that the data 120 is for afull tape storage infrastructure, here shown as including threelibraries 110, 114, 118 but could include more, and is not limited tomonitoring data from a single drive or library.

The data storage system 100 further includes a library management system140 and a cartridge management server 150. For example, the librarymanagement system 140 may include a mainframe or other computer devicerunning an operating system and management software applications 144,with the operating system shown to be MVS provided by IBM and themanagement software being Host Software Component (HSC) provided byOracle, but other operating systems and library management software maybe utilized in the data storage system 100. A data collection agent 146is provided in the data storage system 100 to act to collect librarymanagement-specific (e.g., HSC-specific) data 148 that is transmittedvia IP network 130 to the STA server 160. The cartridge managementserver 150 may run one or more applications 152, such as AutomatedCartridge System Library Software (ACSLS), to control an automatedcartridge system, and cartridge management-specific (e.g.,ACSLS-specific) data 156 is provided by the application 152 over IPnetwork 130 to the STA server 160 for use in analytics of tapeoperations in the tape libraries 110, 114, 118.

Significantly, the data storage system 100 includes the STA server 160that runs or executes the STA application 164 to manage collection andstorage of the data 120, 148, 156 from all the tape analytics datasources in system 100 in the tape analytics data warehouse 168 (e.g., adatabase(s) in memory of server 160 or accessible by server 160) and toperform analytics functions as described herein. Briefly, the STAapplication 164 provides a data warehouse approach to management of atape infrastructure, and this involves gathering/receiving a widevariety of data 166 (which includes data 120, 148, 156 from all sourcesin system 100), storing and processing this data in the database 168,performing analytics on this data such as predicting health issues andperforming validation of the media and drives in libraries 110, 114, 118(e.g., with an MDV module), and presenting out all the data available inthe database 168 including the predictive health attributes and resultsof validation of media/drives as shown at 174 to a user 173 operating aclient node or workstation 170. The client workstation 170 includes amonitor/display device 172 that is operable (such as with a browser) toallow the user 173 to view and process the data 174 via a userinterface, which is described in more detail below. The STA application164 is adapted to allow customer-driven analysis of the data 168 and mayinclude reporting tools, customizable UIs 176, and other devices toenable the user/customer 173 to drive analysis of the tapeinfrastructure in the data storage system 100.

The tape monitoring approach shown in system 100 may be considered adirect library communication approach, which differs from priormonitoring techniques (such as the data path breach approach, the mediavendor lock-in approach, and single library approach). The system 100provides monitoring with data path protection and media vendorflexibility. Also, a single monitoring application 164 may used formultiple library environments 110, 114, 118.

In general, the STA application may be deployed into a customer's/user'senvironment on an IP network (such as network 130). The tape analyticssystem, either an STA appliance or the STA software 164 installed onto aserver 160 belonging to a user/customer, is provided IP connectivity totape libraries 110, 114, 118 and to one or more workstations 170 whereSTA users may use a browser-based GUI 176 to interact with the tapeanalytics system. A number of transport mechanisms may be used tocollect the data 120 from the libraries 110, 114, 118. In one usefulimplementation, the communication link uses SNMP for interactionsbetween the libraries 110, 114, 118 and the STA application 164. Thecommunications with the client workstation 170 may be provided with alink using http and https or the like to run a browser-based GUI 176.Communications to the mainframe 142 and the management softwareapplication 144 and data collection agent 146 may use a protocol (e.g.,a proprietary or a non-proprietary protocol) over TCP/IP sockets or thelike. The system 100 typically is fully under the control of the user173.

The STA application 164 may be thought of as being provided in atechnologies or software stack. From top to bottom, this stack mayinclude: applications; middleware; a database; an operating system; avirtual machine; a server; and storage. The application is the STAapplication 164 and the data collection agent 146, both of which may beprovided in nearly any programming language with one exemplaryimplementation using Java J2EE for the STA application 164 and assemblylanguage for the data collector 146 (e.g., IBM assembly language for anSMF data adapter on mainframe 142). The applications may also includeanalytics such as Crystal Ball (CB) from Oracle for tape analysis. Insome cases, the STA application 164 may be written in Java and useOracle's MySQL, JDMK, ADF 11g, and Weblogic 11g software products, but,again, the description is not limited to such an implementation.

The middleware may be used, in part, to provide a browser-based UI andmay include WebLogic from Oracle or similar application and/or webserver software. The database is used to implement the tape analyticsdata warehouse 168 and may utilize MySQL or similar database managementtechnologies. The operating system may be Linux, Solaris, or any otheruseful operating system provided by Oracle or other OS providers. Thevirtual machine may be implemented using Virtual Box or the like. Theserver also may take numerous forms to practice the system 100 such as aSun Fire server from Oracle or the like. The storage in the technologystack is provided by a tape storage implementation as shown with tapelibraries 110, 114, 118 with tape drives 112, 116, 119. Again, thehardware supported and used in system 100 may be widely varied topractice the tape analytics and monitoring described herein and may takethe form shown in FIG. 1. For example, the libraries 110, 114, 118 maybe Oracle's StorageTek libraries (e.g., the SL8500, SL3000, SL500, orsimilar or future libraries), and the drives 112, 116, 119 may beOracle's StorageTek drives (and media) (e.g., the T10000 A/B/C, T9840C/D) or LTO 3/4/5 from HP and IBM.

FIG. 2 provides a diagram of a software stack 200 with softwarecomponents or technologies that may be provided in an implementation ofan STA product or an STA application 210 provided on an appliance orinstalled on a customer's/user's server. At the bottom of the stack 200,an operating system 220 such as Linux, Solaris, or the like is provided,and the STA application 210 may include STA scripts 212 to performportions of the STA functionality described herein. In the stack 200, adatabase (e.g., MySQL, an Oracle database, or the like) 222 and a weband/or application server (e.g., Web Logic or another usefultechnology/product) 224 are also provided. A STA database module orcomponent 214 is provided in the STA application 210 to manage andprovide the data warehouse/STA database.

The stack 200 may include the Application Development Facility (ADF) orsimilar technologies as part of the web/application server 224, and STAbusiness intelligence 216 with intelligence subroutines 217 are used toprovide business component of the STA application 210 (such as dataloaders, data transformers, data summarizers, data analyzers (includingan MDV module), and alert/report generators). The ADF provides a numberof functions that are well known by those skilled in the arts and areshown as high-level groups of functionality in the stack 200 of FIG. 2.The ADF business components, including the STA business components 216,217, provide an interface into the database 222. Above the ADF businesscomponents, ADF provides three layers defined in the MVC (model, view,controller) architecture, and the STA GUI 218 is implemented using thesethree layers. The STA subroutines (Java enterprise Java beans, forexample) 217 can directly use the database interfaces provided by theADF business components implementing STA business components 216. Partof the functionality of these routines 217 is implemented using theapplication modules that may be part of the ADF business components. TheSTA application 210 may include a database schema for the database 214,222 and may have shell scripts 212 that are used to install and run theSTA system.

FIG. 3 illustrates a functional block diagram of the architecture of adata storage system 300 implementing the storage tape analyticsdescribed herein. The system 300 includes a data source 310, an STAsystem 330, and one or more client workstations or mobile nodes/clientdevices 360. The STA system 330 receives or gathers raw data 326 fromthe data source 310, warehouses in raw and processed/analyzed form in adatabase 344, and presents the data 356 to the user of the clientworkstation/node 360. The data sources 310 may include nearly any datasource useful for monitoring and analyzing operation of a tape-baseddata storage infrastructure. As shown, the sources 310 include mainframedata from a mainframe 312 performing tape library management functionsand also other data gathering applications 320, such as applications runor executed by a server to collect data on individual jobs or functionsoccurring within a tape library 314. Further, the data sources 310include one, two, three, or more tape libraries 314, and the tapelibrary data may include data pertaining to (and provided by) the tapedrives 316, tape media or cartridges 318, and other library componentssuch as robots. The raw data or records from a tape library may includemount records, records of I/O or what occurred while a cartridge 318 wasmounted in a drive 316, and dismount records.

The STA system 330 (e.g., a server connected via a communicationsnetwork to the data sources 310 and client workstation 360) includes aprocessor(s) 332 that functions to execute code or run software toprovide the STA application 340 and perform its methods/processes. TheSTA application 340 has an architecture made up the following five majorcomponents: data adapters 342, a database/data warehouse 344 in memory,analytics modules (including an MDV module) 346, a user interface module348, and alerting module 350. Briefly, the database 344 holds all dataand system configuration information. The user interface module 348generates a browser-based graphical user interface viewable andmanipulated by the user of workstation/mobile device 360, and the userinterface presents tabular and graphical information and performs allconfigurations of the STA application 340. The STA application 340further includes a set of adapters or adapter modules 342 that gathersor receives data 326 from external data sources 310 and transforms itinto a standardized form. The alerting mechanism 350 providesnotification to the user via workstation/mobile node 360 or othercommunication methods when significant events (which may be defined bythe user) are detected by the STA application 340. With this overview inmind, it may now be useful to describe each component of the STAapplication in greater detail.

The database 344 may be considered the heart of the STA application 340.It includes a set of modules that contain related types of data. Twoprimary modules are the “tape system model” and the “tape warehouse.”The tape system model contains a representation of the libraries 314,media 318, drives 316, and other entities that exist in the tapeinfrastructure being monitored/managed with the STA application 340. Theterm “model” is used since this data is only a representation of thereal world, and the tape system model holds not only the current stateof the world but also its history. The tape warehouse module containsdetailed information about what is happening in the tape infrastructure.This starts with the raw data 326 such as that provided when a tape ismounted or dismounted or when an error is detected. The facts stored inthe warehouse/database 344 also include derived results that arecalculated by the analytics or analytical subsystem 346 of the STAapplication 340. These derived facts may span a range of complexity fromsimple calculations based on a few numbers from a specific event to longterm analytical evaluations.

In addition to the tape system model and the warehouse module, thedatabase 344 may also hold the information needed by the STA applicationfor operations. This may include configuration information needed toattach to the external data sources, data staging areas used by the dataloaders (provided by adapters 342) to process the external data 326,information needed to produce reports and graphs provided by the userinterface module 348, alerts and rules needed by the alerting module 350to detect and process alerts, and any other persistent informationneeded by the STA application 340.

The human interface to the STA application 340 is its graphical userinterface provided by the user interface module 348. The human interfacemay be implemented using web browser technology to avoid use of aseparately installed component. The GUI may provide authentication(login) and authorization (permissions) functions to control access tothe stored data provided by the database 344 and system functions. Theuser interface 348 provides the ability to define and view a variety ofreports. Generally, the reports may include tabular and/or graphicaldisplays that show some subset of the facts available in the database344. Various pre-defined (by the STA application 340 or by the user ofworkstation 360) reports and displays are available to view both the rawdata and the analytical results. These reports can be customized, forexample, by filtering the data shown based on either the model data(e.g., to a specific set of the libraries 314) or by the dimensions ofthe fact data (e.g., specific time ranges, after or before a particularevent occurred, data for a particular building or business unit, and soon). Additionally, the GUI provided by interface module 348 may provideadministrative functions useful to manage the STA application 340. Thesemay include configuring data sources 310, managing user access to theSTA application 340 (e.g., to configure LDAP servers or the like),configuring alerts, servicing the STA application 340, and otherfunctions.

The STA application 340 collects and uses data 326 from various externalsources 310. These sources 310 may include tape libraries 314 and amainframe HSC or other tape management system 312. Further, othersources may be provided or added to the system 300 as shown at 320. Thedata loaders or adapters 342 acquire the data 326 by either pulling itfrom the external source 310 or by receiving this data 326 as messagesfrom the external source 310. Either or both mechanisms may be used fora specific source within the set of sources 310. The loaders 342 areresponsible for parsing the input data 326, performing anytransformations needed and inserting the data into the raw fact tablesand model tables of the database 344.

The loaders 342 may work via a two-step process. The first step may beto acquire the input data 326, parse it, and insert it into stagingtables in database 344 (or in other areas of memory accessible by theSTA application 340). The second step may be to perform anytransformations needed to put the data into the standard structure usedin the tape system model and fact module or tape warehouse. The parsedinput data may be retained in the staging tables indefinitely to allowreprocessing of the data, which may be very useful in many cases such asshould issues be found in the data or in the transformations.

The analytics subsystem 346 may include routines/programs that perform aseries of calculations on the raw facts data. These calculations may bepredetermined and/or predefined in some cases. For example, one routineor program may implement a “suspicion algorithm” that analyzes the datafrom the dismount records to determine drive and media health. Theanalytics module 346 may also run an MDV module to perform processes tovalidate media 318 and/or drives 316 of one or more the tape libraries314, with this process described below beginning with FIG. 19 in muchmore detail. The calculations may further include aggregation operationsto produce periodic (e.g., daily, monthly, or another time period)summaries. The calculations, of course, may be driven by the reportsdesired/provided by the user interface module 348. The analytics modules346 work by retrieving the raw facts and existing analytics facts fromthe database 344, performing the calculations, and then storing theresults back into the database 344. The analytics calculations may betriggered by an event, such as loading data or based on a schedule.

Alerts generated by the alerting module 350 represent significant eventsin the tape environment of data storage system 300 that are detected bythe STA application 340. An alert, as managed by the STA application340, may be a direct result of something that happens in the tapeenvironment, such as the report of an error by a tape library 314.Significantly, alerts generated by alert module 350 may also be derivedby the STA application 340 from the input data 326 and/or datacalculated by analytics 346. For example, a suspicion value that exceedsa threshold may result in an alert, with this alert being a predictiveor proactive alert indicating that operational status or health of acomponent of a tape infrastructure (such as a tape drive, a tape media,or the like) will degrade in the near future and its use should behalted or maintenance/replacement should soon be performed.Alternatively, the results of a validation process for a drive or apiece of media may result in an alert being generated by module 350.

Alerts may be created by an alert detection subcomponent of the alertingsubsystem/module 350. This component may have rules for examining thetape system model and facts data in the warehouse module of database 344and then for generating alerts when appropriate. This may be a simplerules-based subsystem that understands a few rules such as filtering andthresholds and applies user-specified or default criteria and its rulesto create alerts. Once generated, alerts may also be stored in thedatabase 344. Screens may be available via user interface 348 to displaythe generated alerts at workstation 360. In many cases, an alert refersto a specific entity in the user's environment, such as a tape drive 316or a tape cartridge or media 318. Alerts may also have a state that canbe “new,” “acknowledged,” or “dismissed.”

A second portion of the alert subsystem is alert notification. Alertsmay have a severity level, which may drive the communication path(s)used by alerting module 350 in providing the alert to a user (e.g., viaan e-mail, via a text message or voice message to a wireless clientdevice, in a report in a user interface, and so on). Alerts may resultin notifications with a GUI provided by user interface 348 and/or ine-mails being sent to users of the STA application 340. A newly detectedalert may result in notification appearing on the screen of any activeGUI. This function is part of the user interface 348 and may simply be amatter of a GUI or interface module 348 actively polling the database344 for new alerts. The e-mail function may be a background taskinitiated after an alert is detected.

The components of the STA application 340 shown in FIG. 3 may beimplemented using a series of Java beans or similar program devices. Forexample, FIG. 4 illustrates portions of the system 300 of FIG. 3 showingmore details of the components that may be used to implement thefunctionality described for the STA application 340 within system 300.For example, the data adapters subsystem 342 may include a set ofloaders 410 for collecting and receiving data 326 from the managementmainframe 312 and from tape libraries 314, and these may be implementedas Java beans or the like that are timed routines that executeperiodically or be message driven that execute as a result of anincoming message 326. The transport mechanism 420 for data 326 may bebased on a protocol such as SNMP (Simple Network Management Protocol),as shown for libraries 314, and the loaders 410 may include data loadersconfigured for such a data transport protocol (e.g., an SNMP informloader, an SNMP trap loader, and SNMP MIB loader). The mainframe 312may, in some cases, utilize a proprietary data transport mechanism 420such as SMF when the mainframe 312 implements MVS to manage thelibraries 314. The received raw data may then be passed from the loaders410 to a series of data transformers 430 adapted for processing thetypes of data provided by each loader 410.

The analytics subsystem 346 may include one or more analyzerroutines/processes (such as an MDV module) 449 for further processingthe transformed tape operations data, and the output of the analyzersubroutines 449 will be stored in the data warehouse of the database andalso will be provided to the alert subsystem 350 as shown. The analyticssubsystem 346 also includes a summarizer module/routine 448 (e.g., atimer bean(s)) that periodically summarizes the transformed data, withthe summarized data being stored in the database and also, whenappropriate, being provided to the alert subsystem 350. The alertsubsystem 350 includes an alert generator 453 for determining when analert needs to be provided and to then generate the alert, and thegenerated alert is provided to an alert notifier 455 for communication356 of the alert to a user such as via an e-mail message to an e-maildestination for receipt/viewing with a client device or node 360.

With regard to the architectural principles of the STA application, itcan be seen that it is database focused, data is to be retained, historyis maintained, data is warehoused, and the STA application is messagebased. First, the STA application is database focused, which means thatto the extent practical all data gathered, transformed, and analyzed isheld in the STA database. Here, “data” is any information received bythe STA application, generated by the STA application, and input by auser. As a result, flat files and configuration files are typically notused. Being database focused also means that knowledge is held in thedatabase when possible. Developers are sometimes faced with a choice ofbuilding knowledge into the code or placing it in the database. Wherepractical, the choice when implementing an STA application is to placeknowledge into the database rather than embedding it into code. However,the function of parsing an input record apart may be better handled incode, but, in contrast, the knowledge needed for converting betweencodes found in that input record and STA meanings typically are placedin the database.

Second, data is retained or held rather than discarded. For example,when a result is computed or data is received, the STA application actsto hold onto or retain the data in its least-processed form. Then, asadditional results are calculated, both the input data and thecalculated results are retained by the STA application in the database.Third, the STA application maintains not only the current state of thetape infrastructure but also its history. This impacts the datastructures because the infrastructure changes over time. Both currentand historical information is stored in the same tables. This allowsqueries to be the same whether searching for current or past records. Aconsequence of this approach, though, is that queries may be morecomplex as queries that only want current data have to screen out pastdata.

Fourth, the STA application is fundamentally a warehouse that capturesdata about a user's tape infrastructure. The STA database may bestructured as a star schema to the extent possible. Because the STAapplication may provide navigation using the familiar hardware hierarchyof tape libraries, the STA database may use a hybrid model, e.g., themajority of the data is in star tables while the hardware hierarchy isin tables that hang off the dimension tables of the star. Fifth, the STAapplication is message based. The STA application has a number ofdifferent functions including loading incoming data into the database,parsing apart the incoming data, and performing computations on thedata. The STA application may use a message-based approach to handlingthese different functions. Once one function has completed its work, itmay send out a message to be received and processed by another functionof the STA application.

At this point in the description, it may be useful to describe the STAapplication and data storage systems implementing this software tool byproviding several functional walkthroughs, e.g., outlines of theworkflow a user would use to perform various functions with the STAapplication. The functional walkthroughs are provided in the followingoutlines: (1) a user model; (2) data viewing; (3) data collection andprocessing; (4) alerting; (5) data source configuration; and (6)installation.

With regard to a user mode, there are several different types of usersthat may use the STA application or a data storage system with such aprogram/tool provided for monitoring tape storage. A basic user may wantto see a simple view of the tape infrastructure using the STA userinterface. Such a user may use predefined views provided as defaultviews in the STA application or may use customized views created byother users. A basic user may navigate from screen to screen as theyview different aspects of their tape environment and investigateproblems. An analytical user may spend more time performing detailedinvestigations of their tape infrastructure. While this type of user mayuse the STA application's pre-defined data views, they will likelycustomize these views (which may then be used again by them or others).This user may export data to other tools for further analysis (e.g.,Crystal Ball or similar tools that may be useful for performing ad hocinvestigations of their data). A report-viewing user may make use ofreports defined by basic or analytical users. Such reports may bee-mailed directly to this type of user such as in the form of pdf orsimilar documents. An administrator may be a user that is responsiblefor the management of the STA application, and such management mayinclude software or appliance installation, configuring data sources,performing backups of the STA database, and installing new versions ofsoftware.

With regard to data viewing, viewing the data elements collected by theSTA application may be considered a core STA function. Data elements maybe grouped into “information sets” that gather related elements.Examples of such information sets may include “drive health” and “mediahealth.” While the STA application is typically focused on drives andmedia, it also collects information about tape libraries and theircomponent parts and is capable in some cases of displaying this libraryand library component information. Data may be displayed in graphical ortabular form, and numerous options are typically provided for selectingthe data to be displayed in the user interface, for controlling whichspecific attributes are displayed, and for modifying the appearance ofgenerated and displayed charts.

At this point, it may be useful to provide an example of user interfaceflow. When a user connects to the STA application (e.g., via abrowser-based GUI or the like), a “dashboard” view is typically shown tothe user on a display or monitor of their workstation or client device.The dashboard gives a summary of the status of the overall system, and amore detailed, but typically still summarized, “overview” is availableto provide more details. From there, the user can choose to investigatedrives, media, libraries, or the various other entities known to andmonitored by the STA application. The user can direct the STAapplication to show a table of many entities, such as a list of drives,in a “multi view.” This data may be summarized by the various attributesin the list into an “aggregate view” or the user may choose to viewdetails about an individual device (e.g., a tape drive) in a “singleview” or the user may view a graph of some attribute of the device(e.g., the drive) over time in a “chart view.” The STA applicationprovides great flexibility in terms of what data is shown and how thedata is presented.

Exemplary flow through the GUI may include the following steps. First,the user may login and once login is validated be presented a dashboardof their monitored tape-based data storage system. The users may noticethat there is a problem with one of the tape drives in one of thelibraries. The user may respond by choosing an aggregate view of drivehealth versus drive type, and this may result in the user determiningthat a number of a particular type of drive is in a “faulty” or otherstate (a multi view of drives). The user may then decide to look moreclosely at the first drive in the list and bring up a single view ofthat particular drive.

From this point, the user may want to see the recent activity of thedrive and choose, for example, to see a time ordered multi view of theexchanges performed by that particular faulty drive. Then, if no obviousproblem is noted, the user may select a line chart of throughput for thedrive, where the user may notice a recent exchange with throughput lowerthan other drives. Then, the user may jump back to the multi view of theexchanges so that they can select the tape media in that exchange byclicking on the volume serial number (“volser”), for example, in thelist of exchanges. This brings up a single view of that particular tapein the user interface. From here, the user may request a list ofexchanges involving that tape and then a line graph of the associatedthroughput. The user may then notice via the user interface-provideddata that the tape media has consistently been producing lowerthroughput than typical for that type of tape media regardless of whichdrive the tape was used with or mounted into within the library. Theuser may than respond by freezing the tape media in their application,leaving it available for reading but blocking any further writes to thatproblematic tape media. Such processing of tapes/media and rives may besignificantly improved upon or replaced with the validation operationsprovided by the MDV module as described herein.

The STA application provides considerable flexibility about theappearance of most of these display screens in the user interface. Thetables shown in a multi view, for example, can be sorted. Selectioncriteria may be applied to limit the entities (e.g., drives) shown.Columns can be reordered and hidden. Similarly, for aggregate views,selection criteria may be applied to limit the data shown. The user maycontrol which attributes are used for columns and rows and whichattribute is used for the cells and how that data item is summarized(e.g., count, sum, average, or the like). The STA application providesthe user the ability to save a screen once it has been tailored to theuser's preferences or user-provided design. Once a user has adjusted thecontent and appearance of a screen, it can be given a name and saved,and a saved view may be made available to other users or reused by thesaving user as the view can be retrieved at any later time. Generally,the view will not retrieve the same data at later dates since new datais continuously being added to the STA database, and the same view, whenretrieved at a later point in time, will show the latest data. A savedview typically only shows a fixed set of results when the view isconfigured with a specific date or date/time range.

With regard to data collection and processing, the STA application orsystem collects data from external sources. For example, data may becollected directly from tape libraries (e.g., SNMP data or data usingother data transport mechanisms) and from a library management system(e.g., SMF data from a mainframe), and the actions of the STAapplication may be similar for these two data sources. Data may beinitially acquired by the STA application by either it being sent by thedata source or it being retrieved from the data source. For mainframedata (e.g., MVS SMF data or the like), an agent (“the MAT agent”) may beinstalled on the mainframe (e.g., on the MVS system or the like). TheSTA application may periodically request data from the MAT agent, andthe MAT agent may retrieve data from the library management system(e.g., from MVS and from the HSC) and send it back to the STAapplication. Some library data (e.g., SNMP data) may be sent in the formof trap or other data (e.g., for SNMP it may be SNMP Traps and SNMPInforms), and additional data may be retrieved from the libraries (e.g.,using SNMP Gets when the data transport mechanism is SNMP).

Once data is received by the STA application, the received data isinserted into staging tables, with these staging tables holding the datain a minimally processed or raw form. Data elements are extracted fromthe incoming data for the staging tables (e.g., the incoming Traps orMIBs for SNMP). Some data may not require any parsing such as the SNMPInforms and SMF records from the library management mainframe. Thisallows the STA application to reprocess input records if moreinformation is desired in a future version or if a problem in the datarequires special processing in some cases. After loading the data intothe staging tables, the STA application acts to transform the stageddata into a standardized form and inserting the transformed results intothe “raw fact” tables in the STA database. This step may requireupdating “dimension” tables such as if a move involving a new tape mediais received. Once the data is in the raw fact tables, analyticprocessing is performed. Some calculations are performed as each newrecord is received, and these are started when new records are insertedinto the raw fact tables. Other calculations/analysis are performedperiodically (e.g., hourly, daily, and the like), and these are run astime periods pass based on rules specified by the STA application(default periods) or the STA application users (user-specified analysisperiods).

With regard to alerting, alerts are typically generated in response tosignificant events being detected by the STA application. In someimplementations, there are at least three sources of alerts including:(1) changes in the top level conditions of libraries; (2) SNMP Traps orsimilar data being received from the libraries; and (3) an input orcalculated value provided by the analytics module being determined toexceed a threshold value. When the STA application detects an eventcondition, it creates an alert record that is stored in the STAdatabase. The STA application may then send notification about the alertto a user of the STA application (or one that has subscribed forparticular alerts). Each alert may have a severity level, andnotification may vary in practice including transmitting e-mailmessages, communicating voice/audio messages to a wired or wireless userdevice, providing a text message, and the like.

Regarding alert configuration, top level conditions and other settings,such as SNMP Traps, may require no configuration. However, thresholdalerts may require that the user specify a variable to monitor and thethreshold for that monitored variable, with such configuration beingperformed via the user interface in some embodiments. Once set up, theSTA application, e.g., with the alert subsystem or module, may check anynew record in the database that contains the specified variable and maycreate an alert when the variable is determined to exceed (or fall belowif so specified) the threshold. Users may also configure notificationrules that are used to specify an alert type and/or severity level andprovide a recipient for the alert (e.g., an e-mail address, a cell phonenumber, or the like). Each time a new alert is created it may becompared to the alert notification rules. If the alert meets the typeand severity criteria set in the notification rules, the alert iscommunicated to the specified recipient (e.g., an e-mail alert is sentto an e-mail address).

Now, turning to data source configuration, the STA data sources may haveto be configured in the STA application and, in some cases, in the datasource before the data will be provided to the STA application. Forexample, the STA application may use a number of SNMP data sources suchas the tape libraries themselves (although other transport mechanismsmay be used). SNMP data sources may require configuration in both thelibraries and in the STA application. In the STA application/system, thesetup may be done using the STA user interface. In each of the tapelibraries, the setup may be done using the command line interface or thelike. To configure SNMP, the user may choose a username, authorizationmechanism, authorization password, privacy mechanism, and a privacypassword. The STA application may have an SNMP “engine ID.” This isneeded in some cases to complete the configuration (and may be displayedin the STA user interface), and the IP addresses of the STA system mayalso be provided as part of configuration. Once configured, the STAapplication begins monitoring for SNMP input (e.g., Traps and Informsand may perform the Gets) while each library will start sending Trapsand Informs to a configured destination based on the list ofTraps/Informs that are specified to be sent (typically, all availableInforms and Traps are sent to the STA application).

SMF configuration (or library management system configuration) mayinvolve actions on both the library management system (e.g., the MVSsystem) and on the STA application system. On the library managementsystem, a data collector agent is installed (e.g., a PTF containing aMAT agent may be provided on the system running HSC or SMC). On the STAapplication system, a connection may be created to each data collectoragent such as via the STA user interface. This may involve specifyingthe IP address or hostname of the system with the data collector agent,a port number, the MVS or other host name, and whether the target systemis running particular host software (e.g., HSC, SMC, or the like).

With regard to installation, the process will depend on whether thesoftware version or product of the STA application or the applianceversion is being installed for a user. If the software-only installationis performed, the STA software is installed onto an existing server orcomputer device, and the installation can be done by the user or as aprofessional service. The server need not be dedicated to the STAapplication, but the server has to have compatible versions of theoperating system, web/application server (e.g., Web Logic), and database(e.g., MySQL or the like) already installed on the server. The serverfurther should have network connectivity to the tape libraries, librarymanagement system, and any other components/tools that will serve as thedata sources for the STA application.

In some embodiments, the STA software is an installable package, suchthat it may be downloaded from a download site. The STA software may runthrough an unpack-and-install procedure where the software componentsare placed into the proper locations on the server and data storagesystem. The STA application is given the information to be grantedaccess to the database. The user performing the install may specifywhether a new database is to be created or if the database alreadyexists (such as after a database restore). If a new database is to becreated, the STA application may create the necessary tables, views, andusers in the specified database. Once the installation is complete, thedata sources are configured as described above, and alert thresholdrules, alert notification rules, and summarization rules can beconfigured.

In other embodiments, the STA application is provided to users via anetwork-ready appliance. The appliance version of STA may be deliveredas a server with the STA application software pre-installed, e.g., aserver physically installed in the user's data center or the like withphysical network connectivity to the tape libraries, library managementsystems, and external SSP (in some cases) being provided. Initialconfiguration of the system may be done, e.g., with a console interface.Then, once sufficient configuration is done to get the STA applianceonto the network, a connection can be made using the web-based interfaceto complete the configuration. On initial power up, the user may connectto the console via the server console interface, and the user providesIP address information. This is typically sufficient to bring up theappliance and its web-based GUI or user interface. The user may nowconnect to the web-based GUI and complete the configuration of datasources, alert threshold rules, alert notification rules, andsummarization rules.

As discussed above, a key aspect of the STA application (such asapplications 164, 210, and 340) is the STA database, which may beimplemented as a MySQL, an Oracle, or other database. The STA databaseholds the data collected and calculated by the STA application as wellas the data the STA application uses to operate. In many ways, the STAapplication functions fundamentally as a data warehouse. The STAapplication does not directly control the tape infrastructure, but,instead, it gathers information about the tape infrastructure, storesand processes it, and presents the data to end users. End users may usethis information to make decisions about the tape infrastructure and maythen make changes or take actions based on the information provided bythe STA application.

In some embodiments, the STA application is designed using the “starschema” approach often used in designing data warehouses and onlineanalytical processing. However, since the STA application has to captureinformation about a user's full tape environment and because theequipment in the user's environment may exist in a hierarchy, the STAapplication may use a hybrid model. In particular, key facts arecaptured in a set of warehouse tables and the hierarchy hardware data iscaptured in a set of normalized model tables, and these two sets oftables intersect.

The STA database (such as database 158, 214/222, or 344 in FIGS. 1-3)may be structured into a series of modules that contain distinct sets ofdata. These modules may include: (a) a tape system model; (b) a tapesystem warehouse; (c) SNMP staging (or library data that is minimallyprocessed); (d) SMF staging (or library management information from themanagement mainframe or the like); (e) transformation tables; (f)analytics tables; (g) alerting tables; (h) localization tables; and (i)STA system tables. Each of these tables is discussed briefly below withmore detailed descriptions following for several of these tables.

The tape system model is a series of tables that hold information aboutthe configuration of the user's tape infrastructure. These tables may beorganized in a normalized form to allow the STA user interface tonavigate through the modeled tape infrastructure. The tape systemwarehouse is a set of tables that capture information from the mount anddismount events that occur in the user's environment (e.g., in theirtape-based data storage system). These tables may be organized in a starschema, and the tables of the tape system warehouse may be used tocapture data about exchanges and moves as well as data derived from theexchange and move data (e.g., by the analytics module of the STAapplication). Moves are individual robotic actions that move a cartridgefrom one location in a library to another. Exchanges encompass two moveswith one being the mounting of a tape media in a drive and the otherbeing the dismounting of the tape media, and exchange data alsotypically captures the data about the I/O performed while the tape mediawas mounted in a tape drive. The warehouse tables typically link intothe tape system model tables to pick up information about the librariesand their components and organization.

The SNMP staging tables capture the information received as SNMP Trapsor Informs and information that is retrieved with SNMP Get operations.These tables contain the SNMP data in a minimally processed form. Insome implementations, individual fields (e.g., variable bindings orvarbinds) are retrieved from the SNMP data and are directly insertedinto the SNMP staging tables. Parsing or transformation is done byreading from a staging table, parsing and transforming the data, andthen inserting the transformed data into the tape system model tablesand the tape system warehouse tables.

The SMF staging tables capture information retrieved from the MVSsystems using SMF records and pseudo-SMF records. SMF records aregenerated by the MVS system and are retrieved by the STA application.The HSC system also generates SMF records. To retrieve configurationdata, the STA application queries HSC for the configuration andretrieves this information in records formatted similarly to SMF records(hence, the “pseudo SMF” label). The SMF staging tables hold theserecords in raw form. After loading into the SMF staging tables, theserecords are read, parsed, transformed, and inserted into the tape systemmodel tables and the tape system warehouse tables.

The transformation tables capture the rules for converting from thevarious input codes (e.g., drive type, media type, and the like) intonormalized STA fields. An example of this is the media codes that appearin the incoming records from SNMP and SMF. One input code, such as“LTO_(—)800W,” implies a media family of “LTO,” a generation of 4, anative capacity of 800 GB, that is a WORM tape (versus a normal datatape or a cleaning cartridge). This mapping is captured in thetransformation tables, and the transformer subroutines (e.g., Java beansor the like) use these tables to decode these codes into theircomponents.

The analytics tables provide the information used to perform theanalytical calculations such as tables that contain the directions forcalculating periodic summaries. The alerting tables contain the alertsdetected by the STA application and the instructions for alertnotification. The localization tables contain the localized values to beused when displaying data values that are to be localized. Values suchas drive health, which may be “good” or “faulty,” may be converted tothe user's locale before being output, and the localization tables holdthe conversion information. The STA system tables hold persistent dataused by the STA application or system itself.

It should be understood that some of the values stored in the STAdatabase are actually enumerations. An example is the drive healthvariable, which can have values such as, but not limited to, “unknown,”“good,” “suspect,” and “faulty.” In database design, these types ofvalues are often held in lookup tables that have integer indexes, andthe integer is used in other tables as a foreign key. Queries would thentypically join to the lookup table and a “Where” clauses may refer tothe lookup table value. Many programming languages provide enumerationtypes that allow a list of meaningful text values to be defined and usedin the code. Some databases, such as MySQL, allow definition ofenumeration types while others, such as Oracle 11g, do not, which mayprevent use of enumeration features. To address this issue, the data inthe database may be stored using short strings rather than integers asis commonly done. This will usually avoid a Join, yet let the code stilluse meaningful values. Where necessary, a “lookup table” may be createdthat contains the list of allowed values. These string values may makeit easier to look directly in the database and make for simpler andcleaner code but are not the values that will be displayed to users ofthe STA GUI nor provided in printable reports. Values shown in the GUIand on reports will also typically be localized.

Returning to the tape system model, the STA database may include a tapesystem model module that maintains a hierarchical view of a user's tapesystem architecture. This module contains tables that capture thevarious physical entities and groupings of physical entities present inthe real world (e.g., in a data center), and these tables may benormalized in practice. The tables of the tape system model maintain ahistory of the various entities (such as a library, a tape drive, a tapemedia, and so on).

Each record in these tables contains a starting date and an end date.The starting date is the date and time when the entity was first seen ordata received by the STA application, e.g., the date/time when the STAapplication first detected an entity being installed or that existedupon STA application loading on a user's server (or installation of anSTA appliance). The ending date is the last date the entity was seen (ordata received for the entity), and the ending date is NULL if, as far asthe STA application can determine, the entity still exists in the datacenter or tape infrastructure. The STA application may identify an enddate when an entity is detected to have new attributes, e.g., a librarywith a particular serial number may be found to have a new firmwareversion and this may cause the STA application to set an end date as theold library record is no longer applicable.

A current view of the user's environment or tape infrastructure can beselected by querying records where the end date is null. Because of thehierarchy and the tracking of the history of entities in the tape systemmodel, a change higher up in the hierarchy will propagate into lowerlevels. In the example from above, when a new record is created for thesame physical library as a result of loading new firmware, all thelibrary's subordinates will also require and be provided new records inthe STA database.

At this point, it may be useful to describe a set of exemplary tablesthat may be utilized by a tape system model module. FIG. 5 illustratesan entity-relationship diagram (ERD) 500 of the model tables along witha few of the warehouse tables where there is overlap for one exemplary,but not limiting, implementation of the STA application. The tapeplexes504 represent the HSC or ACSLS instances (or library managementcomponent) present in the user's environment or data center. The STAapplication may initially have no direct connection to ACSLS and may beunable to determine details about tapeplexes 504 that represent ACSLSinstances. For MVS HSC systems, though, this information is provided,and these records may be accurately created by the STA application. Atapeplex 504 may contain zero or more ACSs.

The tables include a logical ACS table 508, and an ACS or “automatedcartridge system” encompasses a set of drives, media, and storage cells.A characteristic of an ACS is that any tape in the ACS can be moved toany location within the ACS with no human intervention. One tapeplex 504may contain multiple ACSs 508. An ACS 508 may contain one or morelibraries or partitions. An ACS 508 contains libraries if the librariesare not partitioned, but if the actual library is partitioned, then theACS 508 would contain multiple partitions. In some embodiments, an ACS508 contains one and only one partition or one or more libraries. Thisis a consequence of the fact an ACS contains multiple libraries onlywith certain tape library environments (e.g., the SL8500 environment)and partitioning is not supported in such an environment. Note, neitherACSLS nor HSC explicitly deal with libraries such that as far as both ofthese products are concerned, ACSs contain one or more LSMs.

In the ERD 500, logical LSM tables 510 are also provided. An LSM is alibrary or a section of a library. One feature of LSMs is that one robotor a pair of redundant robots can move cartridges anywhere inside theLSM. If a cartridge is moved between LSMs, a pass through-port orelevator is used. Pass-through ports and elevators are robotic devicesthat move cartridges between LSMs. LSMs 510 contain a number of otherentities including storage cells, drives, CAPs (cartridge access ports),and robots. The ERD 500 also includes logical CAPs tables 512, with alogical CAP being a CAP as seen by ACSLS or HSC. Because real librariescan be partitioned and CAPs can be either shared by multiple partitionsor dedicated to specific partitions, a physical CAP in the real librarymay appear as multiple logical CAPs 512 in ACSLS or HSC. The ERD 500 mayinclude a logical LSMs CAPs table 513, which is an association table formapping logical CAPs to LSMs.

The ERD 500 shows the inclusion of tables 520 for physical librarycomplexes. A string is an interconnected set of libraries that areconnected with pass-through ports. In a non-partitioned environment,strings and ACSs are identical. In a partitioned environment, differentpartitions may be accessed by difference ACSLS or HSC servers and, so,an ACS is only a subset of a string. Physical library tables 524 areprovided in the ERD 500, and a library is a physical box containingstorage cells, media, drives, robotics, and electronics. Most librariescontain only a single robot or a pair of redundant robots. Thus, alibrary maps to a single LSM. There are exceptions, though, to thisrule, such as the SL8500 where the four rails of the SL8500 are eachmapped to an LSM. Tables 528 are provided to represent the rails of atape system. For example, in an SL8500 library, there are fourphysically distinct sections. Each has a set of rails that the robotsmove on, and, so, these four sections are called rails. Other librariesmay not have this physical division and, so, are considered to onlycontain a single rail. A key characteristic of a rail is that a tape canbe moved within a rail in a single robotic action.

The tape system model includes physical partitions table 530. Librariesmay be divided into logically separate partitions that are representedin table 530. Partitions are presented externally as if they werephysically separate libraries. The model shown by ERD 500 also includesa physical CAPs table 534, and a CAP or cartridge access port is used toenter cartridges into the library or to eject cartridges from thelibrary. The physical rails CAPs table 536 maps the rails to the CAPs ofa library. A robots table 540 is provided, and a robot in this contextmay be a robotic device within an LSM that moves tape cartridges. Arails robots table 546 is an associate table used by the STA applicationto record connections between robots and physical rails.

The ERD 500 shows a PTPs table 550, and a PTP is a pass-through portthat is a robotic device used to move a tape cartridge from one LSM toanother. A rails PTPs table 556 is provided that is an associate tableused by the STA application to record the connections between PTPs andLSMs. In current library designs, each PTP may be connected to two LSMs.The tape system model shown by ERD 500 also includes an elevators table560. An elevator is a vertically oriented robotic device present inlibraries (such as the SL8500 library) that moves cartridges between therails. Because each rail is treated as an LSM, elevators may beconsidered as pass-through ports (PTPs) in some situations. However,because they are distinct devices, the STA application may, instead,capture them in the table 560 rather than in table 550. The railselevators table 566 is an association table used by the STA applicationto record the connections between elevators and rails, e.g., in theSL8500 library for example each elevator connects four rails.

The tape system model shown by ERD 500 also includes a cells table 570.Each LSM, rail, and partition contains some number of cells. Cells arelocations that can hold a tape cartridge or a tape drive. Various typesof cells exist, including storage cells that hold cartridges, CAP cellsthat are in CAPs and are used when entering or ejecting tapes from alibrary, transport cells that are in robots and are used when a robot ismoving a cartridge, PTP cells that are locations in a rail where a PTPor elevator can grab the cartridge, and drive cells. Drive cells may beconfusing in that there is a large physical location in a library wherethe drive can be inserted and then a smaller location in the drive wherethe cartridge can be inserted, and both are typically identified by thesame numbering scheme.

In practice, it is unfortunate that there are three distinct cellnumbering schemes in use. One is the physical address, which is thelocation of the cell within the physical library. A second is the “HLIaddress used by ACSLS, HSC, and the HLI (host library interface)protocol. This scheme was devised when the only types of libraries werethe Powderhorn libraries and predecessors/variants. The HLI addressesare inadequate to represent the more complex libraries such as theSL8500 and SL3000 libraries. A mapping scheme exists between these twoaddressing methods. In addition, the SCSI medium (or “media”) changerprotocol uses “element IDs” to address the cells. The STA records all ofthese various addresses in some embodiments, though not all may be inuse in any particular cell.

The cells table 570 is also part of the warehouse of the STA database.As such, it contains many denormalized fields. Specifically, all thevarious identifiers from tables such as the LSMs table 510, thelibraries table 524, the partitions table 530, and the tapeplexes table504 are denormalized into the cells table 570. The ERD 500 also includesa drives table 580, and this table represents the physical tape drivespresent in the tape infrastructure. This table maintains informationabout drives such as firmware version, and a new record may be createdwhen this information changes. The drives table 580 is also part of thewarehouse module and contains denormalized fields based on the hierarchyabove it in the tape system model tables as shown in the ERD 500, forexample. The drive cells table 582 is an association table that mapsbetween drives and cells. Each record in this table 582 represents aperiod of time when a specific drive was present in a specific cell. Adrive properties table 584 may be provided to collect operationalproperties of each drive in the tape infrastructure represented by thetape system model.

The tape system model shown by ERD 500 includes a media table 586 thatrepresents tape cartridges (or tape media, media, or tapes). As with thedrives table 580 and the cells table 570, the media table 586 is one ofthe dimension tables for the warehouse and contains a number ofdenormalized fields. A media cells table 588 is included that is anassociation table that maps between media and storage cells. Each recordin this table 588 represents a period of time when a tape is in aparticular storage cell. A new record is created in this table 588 whena tape is placed into a storage cell other than the one where it wasmost recently located. A new record is not created, typically, if a tapeis mounted and then returned to the same cell, but a new record iscreated if the tape is mounted and then moved to a different cell whenit is dismounted.

Further, the ERD 500 shows that the tape system model may include an MVShosts table 590 that is used to represent hosts. Hosts may be physicalmachines, virtual machines, or MVS LPARs. This table 590 may containonly hosts that the STA application receives information about and isunlikely to be a complete representation of all machines in the user'sor customer's environment or data center. The MVS hosts drives table 596is provided as an association table that maintains a mapping betweenhosts and drives. Any particular host may be attached to many drives,and any drive may be attached to multiple hosts, with the table 596containing this mapping. This information may be derived frominformation received by the STA application and may not represent alldrive/host connections actually present in a user's environment or datacenter.

Returning now to the tape system warehouse module or simply warehouse,the STA database may include a warehouse that contains the detailedinformation about the operational activities of the tape libraries anddrives. These tables may be organized in some implementations as a starschema. In a star schema, the center of the star is some “fact,” andarranged around this fact are a number of “dimension” tables thatcontain information about the fact. For example, in the STA applicationdata model, an exchange is a key event for which the STA applicationcaptures data. An “exchange” in this case encompasses mounting a tapeonto a drive, performing I/O on the tape, and then dismounting the tape.The drive captures data about the I/O and the drive performance as theI/O occurs. This data is then passed to the library during the dismountprocess. The library then passes the data to the STA application, eitherdirectly using a transport mechanism such as SNMP and SNMP Informs orindirectly such as by passing the data to HSC which then passes it tothe STA application using SMF records.

FIG. 6 illustrates a diagram 600 of a simplified schema for capturing ortracking data related to exchanges in the warehouse of the STA database.As shown, a table 610 is provided for exchanges as well as tables, asdescribed above with reference to FIG. 5, for cells 570, hosts 590,media 586, drives 580, and drive properties 584. An additional table 620is used as a dimension, and the periods table 620 contains records fortime periods. For the STA application, the smallest period used may beone hour or another useful time period such that there is one record persmallest time period such as one record per hour. These records start atthe point in time of the earliest data in the STA database and willperiodically be populated to some point in the near future. The periodstable 620 may be used to “bucket” the data into time periods to make itmore simple to select, for example, all exchanges that completed on aspecific day or other range of time.

The exchanges table 610 captures data about each exchange. This includesitems such as the start and end date/times for the exchange, the amountof data read and written, read efficiency, write margin, errors, andother information provided by the library and drive. The exchangeinformation may be limited by the interfaces with a high likelihood thatit will grow in size over time. The exchanges table 610 may have anumber of foreign keys to the dimension tables. The foreign keys to themedia table 586 and to the drives table 580 are relativelystraightforward as these are the tape and drive involved in theexchange. Further, the hosts 590 is the MVS host involved in theexchange, and this is available only for the MVS environment. There arethree foreign keys to the cells table 570 because the tape may start inone cell, be mounted into a drive (which is in some cell), and then bemoved to a different cell when dismounted. The two foreign keys to theperiods table 620 are for the period when the exchange started andended.

FIG. 7 illustrates a diagram 700 of a star schema utilized by the STAapplication (or database module) for collecting data pertaining to movesin a tape library. A robotic move is the sequence of actions that movesa tape from one location to another. For example, a library may use theterm “get” to refer to a robot grabbing a tape from a location and theterm “put” to refer to a robot dropping off a tape at a location. A movecould be as simple as getting the tape from one location and then thesame robot putting the tape at another (or the same) location. Incontrast, a move may be much more complex and involve several differentrobots and passing the tape from one LSM to another.

The moves table 710 in the STA application or STA database records theseactions. Regardless of the complexity of the actions required, a singlerecord is typically used to capture each move. Data captured for themove is related to the library actions required, such as the timerequired from the robot(s) and the time the move was queued up waitingfor access to the robotics. As shown, the moves table 710 share many ofthe same dimension tables as exchanges, e.g., the cells table 570, thedrives table 580, the drive properties table 584, the media table 586,and the hosts table 590. A periods table 720 is also provided for themoves table 710. A move may only have two foreign keys to the cellstable 570 because a move has only a source and a destination. A recordin the moves table 710 typically does not have an explicit reference toa drive, though one may be indirectly involved if the source ordestination is a drive. Note, moves and exchanges are closely linked. Anexchange will have two moves, one to mount the tape and a second todismount it. However, moves can be done for reasons other than mountingand dismounting tapes. These include entering tapes (e.g., a move from aCAP cell to a storage cell), ejecting tapes (e.g., move from storage toCAP), or a simple move (e.g., storage cell to storage cell).

FIG. 8 illustrates a diagram 800 of a schema used for the analyticstables in the STA database. The analytics tables 810 are fact tablesthat may be used to store computed facts or results. For example, thecomputed facts/results may be derived from exchanges data from tables610. In such an implementation, the tables 810 may include two separatebut similar analytics tables for use by the STA application. A driveanalytics table may be used to contain results relevant to the drive 580used in the exchange 610 while a media analytics table may be used tocontain results relevant to the tape 586. The relationships from theanalytics tables 810 to the dimension tables (including a periods table820 as well as tables 570, 580, 584, 586, and 590) may be the same asfor the exchange table 610, with the addition of a foreign key into theexchanges table 610. While the various foreign keys other than that forexchanges are redundant, their presence simplifies queries and is inkeeping with the star schema pattern that may be used for datawarehousing in the STA database.

FIG. 9 illustrates a diagram 900 of a schema used for summaries tablesmaintained by the STA application in the STA database (or warehouse).The summaries tables 910, 916 contain data for drives 580 and media 586that is summarized by the STA application (e.g., the analytics module)over some time period 920. The drive summaries table 910 and the mediasummaries table 916 contain data for drives and media, respectively, andthey may contain fields that are similar to the fields in the exchangesand analytics tables 610 and 810. However, while the exchanges andanalytics tables 610 and 810 contain data from a single exchange, thesummaries tables 910, 916 typically contain data for a longer timeperiod.

The relationships for the summaries tables 910, 916 are simpler than forthe analytics and exchanges 610, 810. This reflects the fact that manyor no exchanges may have contributed to the summary. Summaries 910, 916have a relationship to a granularities table 918, which contains entriesfor hours, days, weeks, and so on. The foreign key to the granularitiestable 918 gives the length of the time period for the summary 910 or916. The foreign key to the periods table 920 is for the period record(e.g., an hour) for the start of the time period.

The STA database may also utilize staging tables to hold data as thedata loaders receive it from the data sources. The loaders are describedbelow in more detail along with explanation of the data adapter(s) ofthe STA application. The staging tables may hold the data in arelatively raw form. In other words, each loader may receive or retrievetape operations data and perform minimal processing on the receiveddata. The transformer module or portion of the data adapter will thenread the data from the loader tables, perform any necessarytransformations, and then insert the standardized or transformed datainto the warehouse and tape system model tables. The staging tables maytake the form of SNMP staging tables and SMF staging tables in someembodiments.

Transformation tables may be provided in the database to be used by thetransformers of the data adapter to standardize data. One of the stepsperformed by the transformer (e.g., a transformer bean or the like) ineach of the data adapters may be to transform the data from input forminto a standardized form. Part of this transformation is to convert fromthe short codes used in the libraries and related software intomeaningful terms. The transformation tables may contain the inputversion of the various codes along with the standardized values. Thetransformer then will use the content of the transformation tables tomake the mapping from the raw input code into the standardized values.

The database of the STA application may also include alert tables, andthe alert tables may include a set of tables that hold informationrelated to alerts. The usage of the alert tables is described in moredetail in sections explaining operation of the alerting subsystem of theSTA application. The set of alert tables may include an alerts tablethat contains the alerts generated by the STA application. An alertactivities table may be provided that contains the history of eachalert, which may include when an action was taken on an alert and whichuser performed the action. An alert threshold rules table may beincluded that holds the rules that specify when an alert is to begenerated when some drive or media value crosses a threshold.Additionally, the alert tables may include an alert e-mail notificationrules table (or other alert communications table) that holds the rulesthat specify when an e-mail message is sent when an alert is generated.

The STA database is used to retain both current and historical data fora tape infrastructure. That is, not only does the database capture thecurrent tape infrastructure, it also captures the infrastructure as itexisted at any point in time in the past. This information is maintainedin the same tables regardless of whether it is the most currentinformation or older information, which allows the STA application tomaintain a continuous history of the tape infrastructure. Becausecharacteristics of devices can change over time, the STA application hasmany records for one physical device. For example, one of the attributesof a tape drive is its firmware version. When the firmware for a driveis updated, the STA application creates a new record in the model drivestable for that drive. Unchanged characteristics, like a serial number,are the same as in the previous record, and the changed characteristicsare placed in the new record.

Begin and end data are typically kept in each record so as to allow theSTA application to provide a continuous history for each device and toshow the exact parameters in effect at any point in time. When a changeoccurs and a new record is created, the ending date/time for the oldrecord and the beginning time for the new record are set. Ideally, thesewill be set to the actual time of the change if the STA application hasthe correct time, but, if not, the STA application may use the data andtime when it detects the change as the end time for the old record andthe begin time for the new record.

The changes preferably propagate through the hierarchy of records in theSTA database. In the above example, not only will a new model driverecord be created for the updated drive but also a new model drive cellsrecord (see attached figures) will be created to link the new driverecord to its proper cell. When a change occurs higher in the hierarchy,the effects are more dramatic. For example, a change in the firmwareversion of a library may require new records be created for all thedependent records. The need to create new records stops when the processreaches an association table. For example, with reference to theattached figures, when the library firmware changes, new cells recordsare created to link up to the new library record. New media records, onthe other hand, are not required as the media does not change, but,instead, a new model media cells association record is created thatlinks the existing, unchanged media record with the new cells record.Such an arrangement allows the STA application to track the exacthistory of each monitored entity, and it also allows actions performedin the tape infrastructure (e.g., moves and exchanges) to be tiedexactly to the configuration in place when the action occurred. When anexchange occurs, it will be linked by its foreign keys to the specificdrive record that is most current when the exchange occurs. After achange occurs (e.g., to the drive firmware) and a new record is createdin the drive properties table for the drive, new exchanges will tie tothe new record that contains the new drive firmware version, and oldrecords will tie to the old record that contains the old firmwareversions.

The STA application will likely deal with a variety of data sources. Thespecific data elements received by the STA application will depend onthe data source and on the specific type of device that is sending thedata. In particular, the SNMP and SMF data sources send many of the samedata elements, but each sends a few unique items. Further, the specificdata elements returned by tape drives depend on the type of tape drive,with many older tape drives (e.g., 9940, LTO gen 1 and gen 2) producingvery little data. The libraries holding these drives can provideinformation that mounts have occurred to these drives, but the drivesmay not provide the detailed data that newer drive typically produce.Hence, the possibility of missing or sparse data may be considered andaddressed in some implementations of the STA application. When a dataelement is unavailable, the field of a record in the STA database may beset to NULL, and this allows all other parts of the STA application toknow that a NULL value means the data is unavailable.

The data adapters are aware of the exact data being processed. Whenreading records produced for older devices, the data adapter should alsobe aware of how missing data is represented. In the SNMP Informs, forexample, numeric values are modified such that a zero value means thereis actually no data. Non-zero values represent actual data, but thevalue is one more than the true value. Thus, the data adapter isresponsible for inserting NULL for a zero input value and subtractingone from non-zero values before inserting the value into the database.When doing calculations in the analytics subsystem, calculations thatrequire inputs where data is unavailable will be unable to produce theoutput result. The analytics subsystem may be adapted to insert a NULLinto the database for calculations that cannot be performed. When doingoperations such as summarizing the total amount of data read or writtenin a library, the summarization module may include data only forexchanges that provide data. If the library contains older (so-called“unsupported”) drives, the summarized result may include data only forthe newer (so-called “supported”) drives.

It may also be useful for the user interface module of the STAapplication to be configured to deal with missing values. For example,in tabular displays, missing values may be displayed as “NULL” or“unknown” or an appropriate icon. In graphical displays, missing valuesmay be handled in different ways depending upon the graph. In somecases, treating the value as zero may be appropriate. For example, a piechart that shows the total bytes read with a pie slice for each drivetype may show zero as the value if the customer has unsupported drives.In other cases, it may be appropriate to omit the data seriesaltogether. For example, if a line chart is made that shows daily totalsof bytes read, with a different line for each type of drive, it may beappropriate to omit the line for unsupported drive types.

With the database (e.g., database 188, 214, 344) understood, it may beuseful to explain exemplary implementations of data adapters (e.g.,adapters 216, 217, 342) and their functionality in an STA application ofthe present description. The data adapter subsystem of the STAapplication functions to receive data from an external source and/or toretrieve data from an external source, and the data adapter subsystemalso performs any necessary transformations and stores the transformeddata in the STA database.

In one embodiment, the data sources supported are SNMP data sources andSMF data sources. For example, SNMP (Simple Network Management Protocol)may be used as a data transport mechanism to provide a direct link totape libraries of a user's data center. The STA application may use theSNMP protocol (or other transport mechanism) to gather data about thelibraries, drives, and tape media that are present in theuser's/customer's environment or tape infrastructure that is beingmonitored/managed. The STA application may also receive information fromthe libraries via SNMP traps and Informs about actions performed by thelibrary. For mainframe-attached libraries, data may also be gathered bythe data adapters from the MVS SMF subsystem (or other similartechnology) and passed by the data adapters into the STA application forstorage and analysis. The data provided by these two data sources may besimilar, and there is considerable overlap in the individual data itemsprovided by the two sources. However, it is useful to collect both setsof data as each source provides some data not provided by the other.

Each of the data adapters may follow the same pattern. A loader eitherreceives the incoming data records or requests them from the externaldata source. The loader places the incoming records into a staging tablein the database. The loader then sends a message to the transformer toprocess the new records. The transformer retrieves the new records fromthe database, performs the processing necessary to transform the data tothe STA data model, and inserts the records into the tape system modeland warehouse tables. The processing performed by the transformer mayinclude parsing apart text records, converting from text to numbers ordate/times, and performing calculations to convert the data from inputmeanings into the standardized STA model. The transformer alsoidentifies the correct records to use as foreign keys when inserting newdata into the STA database. In some cases it may be useful to retrievenew configuration data in order to populate reference tables or tosynthesize records needed to satisfy referential integrity constraints.

FIG. 10 illustrates a portion of data storage system 1000 implementing atypical data adapter with a loader 1020, a transformer 1024, and dataaccess objects 1028 (see, also FIG. 2 for ADF BC 216). As shown, theloader 1020 receives 1012 or requests 1014 data records from a datasource 1010, and this data is stored in staging tables 1032 in database1030. Then, the transformer 1024 processes and transforms this data asneeded to be suited for tape system model tables 1034, and also thetransformer provides portions of the received data as raw or lessprocessed data to raw facts tables 1038 of the warehouse tables 1036.The model tables 1034 and warehouse tables 1036 are then made availableto the analyzer module (which may include a MDV module/routine asdescribed herein) 1040 and alert generator 1050 for further processingor use as described in more detail in other portions of thisdescription.

Because two or more different data adapters are provided that processrecords from two or more different data sources, each adapter may findthat the data it is attempting to load is already in the database. Thishappens because one event, such as a tape dismount, will cause recordsto be generated by two or more of the input data sources, and such aduplication of input data is a problem that needs to be addressed by thedata adapter subsystem. While the events that the STA applicationcaptures have identification information associated with them, theidentification may not be unique. For example, a specific tape may bemounted on the same drive twice in quick succession. A dismount event isgenerated each time the tape is dismounted. These events propagate tothe STA application through both the SNMP data source(s) and the SMF(for mainframe tapes). This means the STA application will receive fourrecords for the two events. The identifiers in the records, e.g., volserand drive serial number, will be the same. Further, there is noguarantee that the STA application will receive the four records in anyparticular order. To further complicate matters, the date/time stamps inthe incoming records are typically set by different clocks and may beoffset. The reconciliation steps in each of the data adapters, thus,preferably is adapted to consider these complexities when determiningwhether or not a pre-existing database record matches with a new one.

The SNMP data adapter retrieves data directly from the tape libraries.It is the source for data about the libraries, their components, and alldrives and media in the library. The SNMP data adapter handles eachlibrary independently. For example, in a SL8500 string, the STAapplication connects to every library in the string and retrieves data,and it uses the data about pass-through ports to assemble connectedlibraries into a string. The SNMP data adapter typically does notconnect to either ACSLS or HSC, and it, therefore, is unable to provideany information captured in these two systems. The SNMP data adapteruses the SNMP protocol to interface directly to the tape libraries. TheSNMP data adapter may handle at least the following three types of data:(1) the configuration data (e.g., libraries, drives, cells, and tapes)that can be retrieved using the SNMP Get function; (2) the event data(e.g., warnings and errors) that are received from the library in theform of SNMP Traps; and (3) the dismount and move data that are receivedfrom the library in the form of SNMP Informs.

The Traps and Informs are received asynchronously by the STAapplication. The Get data is retrieved by the STA application. Thismeans that two distinct loaders (e.g., loader beans or the like) aretypically used in the data adapters with one receiving Traps and Informsand with another one that is executed to retrieve the Get information. Asingle SNMP transformer (e.g., a bean) may process the data from thestaging tables and move the data into the warehouse and the tape systemmodel.

The STA application may use an SNMP Trap loader process thatcontinuously waits for incoming Traps. When a Trap is received, thevariables are extracted from the Trap and inserted into a staging table.In some cases, several different staging tables are used in the STAdatabase. The dismount/mount/move Informs all have a similar structure,with the bulk of the data being contained in single string. The otherTraps can be grouped into sets of traps that have a similar structure,and each Trap in the same set is loaded into a single staging table.Once the incoming Trap has been inserted into the staging table, theTrap loader sends a message to the SNMP transformer.

The SNMP Get loader runs on a scheduled basis and also in response toevents (e.g., SNMP Traps) received from the library. The interval may bevaried to practice the STA application, but it may be limited by theload created on the library when walking the full MIB. The SNMP Getloader runs frequently in order to ensure the library is still active,but it will only typically retrieve the top set of MIB data. The fullMIB is retrieved at less frequent intervals. The STA applicationreceives a specific Trap when the configuration of the library changes.When this occurs, the SNMP Get loader retrieves the full configuration.However, some of the data fields available in the SNMP MIB are countersthat increment continuously. Retrieving these counters at uniforminterfaces results in more meaningful data. The SNMP Get loader alsoruns immediately when the STA application becomes aware of a newlibrary. The SNMP Trap loader uses a series of staging tables for thevarious components of the library (cells, drives, elevators, and so on).Once a Get operation has been performed for a library, a message is sentto the SNMP transformer.

When the SNMP loader detects a library is non-responsive, it recordsthis in a library status table. It may be possible to hold this in thesame table as the SNMP “top level condition” record. The SNMP loadercontinues polling the library, possibly at a faster frequency thannormal. When the SNMP loader detects the library is again responding, itrecords this fact and then immediately may perform a full MIB walk.Because the library cannot retain Traps and Informs for more than ashort time, the library being inaccessible to the STA application mayresult in some lost data.

The SNMP transformer reads the SNMP staging tables and inserts thedesired data into the warehouse and tape system model tables. Thetransformer is responsible for parsing apart the dismount/mount/moverecords and extracting the various data elements. The transformerlocates the correct records in the dimension tables that define theforeign keys for the new Exchange or Move record. The SNMP transformercreates dimension records, when needed, such as if the record cannot belocated. The SNMP transformer also handles the event traps, whichtypically translate into status records that hang off the tape systemmodel. Another function of the SNMP transformer is to use the Getrecords to update the tape system model.

The SNMP transformer sends messages to the analytics subsystem toperform calculations using the Exchange and Move records and sendsmessages to the alert modules to evaluate new status events. The SNMPtransformer is responsible for updating the tape system model andwarehouse tables when the retrieved or received SNMP data differs fromthese tables. This will happen when a new library is detected, forexample, and the SNMP transformer builds the initial version of alibrary's STA records. However, since communications between the libraryand the STA application may not be fully reliable, the SNMP transformermay at any time detect inconsistencies. In particular, if some Informrecords are lost, such as during a period when the library is unable tocommunicate with the STA application, the STA application may have outof date locations for tapes. The full MIB walk will return currentlocations, and the transformer uses these to correct tape locations.However, the SNMP transformer preferably retains order of input data.Because walking the full MIB does not happen instantaneously and becauserobotic actions may occur after the MIB data is retrieved but before itcan be processed, the SNMP transformer is adapted to avoid using staledata to override a move or exchange that occurred after the MIB data wasretrieved but before it was processed.

The STA's SMF data adapter retrieves data about the tape infrastructurefrom the mainframe systems used for library management. The SMF dataadapter retrieves data, albeit indirectly, from the HSC that runs on theMVS mainframes that are connected to many tape libraries. While the SMFdata adapter provides additional data specific to mainframe tapeoperations, it is able to provide information only for those parts ofthe tape infrastructure known to the HSC system.

The SMF data adapter utilizes a data collector agent or “MAT agent”(which may be considered part of the STA application in some cases),which is installed on the MVS host that is running the HSC system. Thedata collector agent extracts data from the MVS system and HSC andconstructs records in SMF format that are sent to the SMF loader uponrequest. In some cases, only the fields in the SMF records that are ofinterest to the STA application are typically filled in. The SMF loaderis a timed routine (e.g., a timer-driven bean). Periodically, it sends arequest to the data collector agent for new SMF records. The datacollector agent returns records created since the previous retrieval.Because the STA application attempts to run in near real time in manyimplementations, these retrievals are done frequently (such as on theorder of every few minutes). The SMF loader places the SMF records intoan SMF staging table.

Under normal circumstances, the SMF loader requests SMF records relatedto mount and dismount events. However, when the library configurationchanges, a special record called a “Significant Event Notification”record will be inserted in the record list sent by the data collectoragent. The data collector agent sends this as the last record in a batchand holds onto any SMF mount or dismount records generated after theconfiguration change. Hence, the SMF loader has to watch for thisrecord, and if the record is present, the loader sends a request for theconfiguration information. This is also delivered in the form of SMFrecords, which may be better described as “pseudo SMF records” as theyare synthesized by the data collector agent and are not generated by theMVS SMF system. Once these configuration records are received and storedin the staging table, the SMF loader makes another request for normalSMF records.

The SMF transformer parses apart the stored SMF records. It inserts orupdates records in the warehouse and tape system model sections of thedatabase. The SMF transformer locates the proper records to use asforeign keys for the fact tables, and it synthesizes these if necessary.The SMF transformer sends messages to the analyzer module of the STAapplication once it has inserted new records into the warehouse tables.

With regard to reconciliation between the SNMP and SMF data adapters,both the SNMP data adapter and SMF data adapter have access to some ofthe same information. Therefore, tape operations that are specific to amainframe system that is connected via the SMF data adapter result inrecords being sent to both data adapters. Because there are unknowntiming delays in both of these data paths, the STA application cannotmake assumptions as to which variant of a record arrives first.Therefore, both transformer functions are typically written to handlethe fact a record for a move or an exchange currently being processedmay in fact have already been inserted into the database.

Both transformers locate the correct records in the dimension tablesprior to inserting a new move or exchange record. This may be done byusing identification information, such as drive serial numbers, to querythe dimension tables to locate the correct dimension table record. Thesekeys are then used to insert into the Move or Exchange tables. Ratherthan blindly inserting the new move or exchange record, the transformerstypically query first to determine if the record already exists.However, it is possible that over time there will be many records in theMove and Exchange tables with the same foreign keys. When querying todetermine if a match exists, the transformers may include other fieldsthat will be the same for the two versions of the data yet are unlikelyto produce matches with older records. These include fields such as theamount of data written and the number of errors. As a final check, if arecord is found, the transformer may check the time. If it is “recent,”the existing record may be taken as a match and updated with the fieldsknown only to the transformer processing the record. Otherwise, the newrecord may just be inserted into the tables/database. The time periodthat constitutes “recent” may be determined once time delays of the twodata paths are understood for a particular STA applicationimplementation.

As discussed previously, the STA application includes an analyticssubsystem (e.g., analytics subsystem 346 shown in FIGS. 3 and 4) thatperforms computations on the raw input from the data sources (e.g.,after processing by the transformers of the data adapter module). Thesecomputations take two general forms: event based and time based. Eventbased calculations or analyses are performed when input data isreceived, and the results align with the input data. Therefore, theyreflect events (e.g., mounts or dismounts) that occur in theuser's/customer's tape infrastructure. Time based computations are basedon the passage of time, and these computations reflect summarizations ofwhat has occurred during predefined or user-defined time periods.

FIG. 11 illustrates in schematic or functional block form a portion ofdata storage system 1100 implementing an STA application, with theanalytics subsystem 346 and its operations being stressed or shown inmore detail. FIG. 11 builds upon FIGS. 3 and 4 with like elementsprovided matching reference numbering and only explained in detail againwhere appropriate. As shown, two modules or tools 448, 449 (which may beprovided as Java beans or the like) form the core of the analyticssubsystem 346. The analyzer 449 is message driven (e.g., amessage-driven bean) and may include an MDV module as discussed belowbeginning with FIG. 19.

During operation of the system 1100, transformers 430 from the dataadapter subsystem send messages to the analyzer 449 as new data isinserted into the warehouse tables 1170 and tape system model tables ofthe STA database 344. The analyzer 449 reads the raw data from raw factstables 1172 and computes the analytics, which are then saved in thedatabase 344 in the analytics tables 1174 in the warehouse 1170. Thesummarizer 448 is time based (e.g., a timer-driven bean), and it runsperiodically. The summarizer 448 reads data from the raw facts tables1172 and the analytics tables 1174 of the warehouse 1170 from the STAdatabase 344, and, in response, it computes sets of summarized resultsthat are stored in the warehouse 1170 in summary tables 1178. Theanalytics results in tables 1174 and the summarized results in tables1178 as well as portions (or all) of the raw facts in tables 1172 may beselectively viewed by user via the GUI 1180 generated by the userinterface module (e.g., module 348) of the STA application. Further, theanalytics results and summarized results may be used be used by thealert generator 453 as input to determine when to generate an alert.

The specific analytic calculations performed may be built into theanalyzer 449. An end user may be able to edit some analytics parameters1150 used in the analytics calculations. An example is the “how manystrikes until you are out” parameter used in a suspicion calculation.These parameters 1150 are given reasonable default values, and thedefault or currently defined parameters may be viewed and edited in theGUI 1180 by the user of the STA application. When these parameters 1150are changed via the GUI 1180, all analytics calculations by the analyzer449 may be recomputed to reflect the new values. While this may meansignificant computation by the STA application, it avoids adiscontinuity of data that would be present if existing results thatwere computer with old parameter values 1150 were kept in the database344 in tables 1174 in the warehouse 1170 while new values were beingcomputed with different parameters 1150 and stored in the analyticstables 1174.

The summarization rules 1160 control when summaries are created, by thesummarizer 448, and for what period of time. Summaries are computed fora specific time period, such as an hour, a day, or a month. The STAapplication is told what intervals to use for these computations andwhen to start the calculations, and, in this regard, a set of defaultrules 1160 may be provided with each installed STA application. Forexample, a default rule 1160 may cause the summarizer 448 to computeboth drive and media summaries stored in tables 1178 on a daily basissuch as each night (e.g., at midnight or the like). Another rule maycall for summaries to be computed over a user-specified number of daysor computing weekly summaries every night (e.g., a moving average).

The summarization rules 1160 may be viewed and edited by the user viathe GUI 1180. Summaries are computed by the summarizer 448 based onthese rules 1160 shortly after each set time period ends. A small delayof a few minutes or less allows for any records that are “in flight” atthe end of a summary period to be received from the transformers 430 andprocessed by the analyzer 449 and summarizer 448. When a summarizationrule 1160 is added or modified, summaries will typically be recomputedfor past time periods, then summaries are computed for future times aseach time period ends. When a summarization rule 1160 is deleted, allsummaries computed using the rule may be deleted from the tables 1178 ofthe warehouse 1170.

Before turning to the alerting functions of the STA application, it maybe useful to describe the analytics function in more detail as may becarried out by the data analytics subsystem in conjunction with the userinterface module (and, in some cases, the alerting module). Theanalytics subsystem may in some embodiments function to monitor and evenpredict media and drive health and to perform media and drivevalidation. It may identify questionable media and drives as well astracking/reporting drive resets and annotations. The analyticsinformation may be shared, in some cases, with ACSLS or similar systems.The analytics subsystem may also determine runtime performance, withthis data then being viewed and organized via the GUI. Such runtimeperformance may include determining host software runtime statistics andqueuing runtime statistics (with some calculations based on ACSLS orsimilar information shared with the STA application).

The following are representative examples of outputs or results of thedata analytics subsystem. With regard to tape media, the analyticsresults (or at least gathered and/or summarized data) may include: lifeof media; loading; read efficiency; write efficiency; repositioning;permanent errors, media degradation; search versus RW; tape idle versusactivity; signal quality; block error rates; and bad data. With regardto tape drives, the analytics, summarized, and raw (or reported) datamay include: life of drive; life of servo/servo tracking errors;cleaning required; data throughput efficiency; permanent errors; drivesubassembly; drive degradation; servo degradation; and environmentaldata. With regard to a library, the analytic or gathered/reported datamay include: cartridge state; cartridge configuration; mediadegradation; drive state; drive configuration; library events; librarycapacity; library topology; partition information; library diagnostics,and environmental data.

The data analytics subsystem typically will support drive and mediatrending analysis. This may include aggregating drive and mediastatistics from multiple sources to provide an overview of the entiretape infrastructure or data center environment. The trending analysismay also produce a comprehensive set of historical statistics includingread/write, performance, capacity, exchange, and cleaning metrics. Alldrive and media data is then stored for the life of the managed deviceso as to provide depth for trending analysis.

The data analytics subsystem also supports drive and media health andvalidation analytics. This may include generating health indicatorsrepresenting a simplified view of the current state of managed devices.The health indicators may be generated through one or more algorithms ormethods that utilize the historical performance of the monitored/manageddevices in the tape infrastructure. These health indicators may also bedesigned specifically to highlight potentially vulnerable devices in auser's environment, e.g., devices that should be proactively replaced ormaintained to avoid potential future problems in operation of the tapeinfrastructure.

The alerting module (such as module or subsystem 350 in FIGS. 3 and 4)of the STA application is used to support remote management of thehealth of a tape environment. The alerts may generally be thought of asincluding library and drive reports (which may be sent to the user orprovided in the GUI) and also e-mail, text, voicemail, or othernotifications (which may be sent to one or multipleaddresses/recipients). Alerts generated by the STA application typicallyrepresent significant events in a monitored tape infrastructure. The STAapplication examines the data received from the external data sourcesand from its internal calculations by the data analytics subsystem todetermine when an alert situation has occurred. When such a situationoccurs, the STA application creates a record for the alert in itsdatabase, and then the STA application may send a notification, e.g., ane-mail or other message about the alert to one or more alert recipients.Alerts may also be viewed in the GUI, and the state of the alert may bemodified by user via this GUI.

FIG. 12 illustrates a functional block or schematic illustration of aportion of a data storage system 1200 implementing an STA application toprovide alerts via the STA alert subsystem 350 to end users (via GUI1180 and messages 356 received on a client communication device 360).This figure builds upon FIGS. 3, 4, and 11 with like components havinglike numbering. The alerting subsystem 360 as shown includes two messagedriven modules in the form of an alert generator 453 and an alertnotifier 455 (e.g., message-driven beans or the like). “Alerts” arecreated by the alert generator 453 and stored in the alert tables 1294of the STA database 344.

During operation of the system 1200, the alert generator 453 receivesmessages from the transformers 490, the analyzer 449, and the summarizer448, with these messages being created after these other modules (orbeans in some cases) update the database 344 (including the warehousetables 1170 and tape system model tables 1290) with new records. Thealert generator 453 reads these records and determines if an alertshould be generated based, in part, on alert threshold values stored intables 1292 of database 344. If so, the generator 453 creates a newalert record for alert tables 1294 of database 344 and sends a messageto the alert notifier 455.

The alert notifier 455 reads the alert, e.g., in the table 1294, and thealert notification rules in tables 1298. Then, if appropriate, the alertnotifier will send a communication or alert message 356 (e.g., an e-mailmessage) about the alert to the specified destinations/recipients forreceipt/viewing on client device (e.g., a wireless communication device,a personal computing device, or the like). The GUI 1180 may also beoperated by a user interface module of the STA application to displayalerts and allows the status to be updated/changed by the user. The GUI1180 may also be used to create, update, and delete alert notificationrules in tables 1298 of the STA database.

In some embodiments, the alerts have one or more of the following dataelements: (1) a severity level; (2) a type, which gives a method forgrouping alerts (e.g., similar alerts, such as drive alerts, may havethe same type); (3) a reference to some entity in the model or warehousetables, such as a drive, a tape media, or a library; (4) a simple statevalue, such as new, acknowledged, or dismissed; (5) a user-enteredannotation; (6) a data and time that the alert was created; and (7) ahistory of the changes to the alert.

The alert generation module 453 may be rule-driven (e.g., a rule-drivenbean that implements a small number of hardwired rules). For example,the alert generator may utilize one or more of three alert generationrules. First, a generator may alert upon library top level conditions.This rule may state that when the “top level condition,” as defined inthe library MIB or the like, changes that an alert is created. The typeof this alert may be “Library,” and the severity may be determined bythe top-level condition. For example, normal may translate to “Info”severity, degraded may translate to “Warning” severity, and notoperative may translate to “Error” severity.

Second, the generator may use a device rule to process SNMP Traps from alibrary. For example, Error and Check traps may result in “Error”severity alerts. Warning traps may result in “Warning” severity alerts.Information and Good traps may result in “Info” severity alerts. If aspecific device can be identified, such as a drive, the type of thealert may match that device type, but, if not, the type may be set to“Library.” Third, the generator may use a threshold rule to processdrive and media analytics and exchange data. The user can specify anyattribute from the analytics or exchanges records to monitor along witha threshold and direction. The user may also specify a severity levelfor the alert. When the alert generator observes the specified attributecrosses the threshold in the specified direction, an alert is generated.The type of the alert may be set to “Drive” or “Media” while theseverity may be the specified value of the rule.

The alerts are inserted in the alerts table in the STA database 344, anda message is sent to the alert notifier 455 to determine if an alertmessage 356 should be sent. The alert notifier 455 uses the alertnotifier rules in table 1298 to determine if a message should be sent(along with what form the message should take (e.g., an e-mail, a textmessage, or the like) and to which recipients/client devices 360). Theserules include an alert type, a severity level, and a recipient (e.g., ane-mail address). When a new alert is generated that matches the alerttype and severity in the rules of tables 1298, an e-mail or other alertmessage 356 is sent to the specified address.

The functionality of the GUI 1180 that is related to alerts allows auser to view a list of alerts (e.g., in a multi view), to view a singlealert (e.g., a single view), to edit the status of the alert, and toinsert an annotation on the alert. The GUI 1180 allows the user tospecify the threshold limits in tables 1292 in the database 344 (e.g.,whether to watch drives and/or media, an attribute to watch/monitor, thethreshold value, the crossing direction, and the severity level). TheGUI 1180 also allows the user to create, edit, and delete notificationrules in tables 1298.

The STA user interface module/component (e.g., elements 218, 348 ofFIGS. 2 and 3) of the STA application (e.g., application 164, 210, 340of FIGS. 1-3) functions to provide a unified tape monitoring interface.It may deploy a unified interface, such as a GUI on a personal computeror other client node or an interface on a mobilecommunications/computing device, that delivers a complete view across anentire tape complex or tape infrastructure of a data center. The userinterface can be used by a data center manager to monitor libraries,drives, and media that may be provided in a single location or begeographically distributed (and/or remote from the manager using theuser interface).

In some embodiments, the user interface module of the STA applicationprovides a browser-based GUI. In other words, a user/customer may accessthe STA GUI using a compatible web browser on their client node/device,which is linked to a digital communications network. The user may enteran IP address or the hostname of the STA appliance or server when theSTA application software is installed. Once the user enters valid logincredentials (e.g., userlD and password), they may be presented with adashboard or overview screen. This screen may give a limited set ofimportant information about a monitored tape infrastructure. From thisinitial screen, the user may drill down to more detailed informationabout the tape infrastructure.

The STA application may include focused views into a tape environment,and these may include specialized reports provided in the GUI. Thespecialized reports may be designed to simplify viewing and reviewingperformance, health, read/write, capacity, and cleaning data elements sothat a viewer/user of the STA application can quickly identify and focuson targeted areas within a tape environment. Report templates may beincluded that provide suspect drive and media reports. The STAapplication and its user interface module may provide pre-loaded/defaultreporting views in its GUI/user interface, but many embodiments also aredesigned with the flexibility to meet the needs of unique tapeenvironments. With this in mind, the user interface module may enable auser to create and save their own report templates that are customizedto suit their tape infrastructure and management/monitoring needs.

In operation, the STA application monitors and collects data about anumber of entities. Examples include very concrete entities such asdrives and media as well as abstract entities such as exchanges (e.g.,the data about a cycle of a tape mount, I/O, and dismount) and analytics(e.g., the results of calculations performed on the data from anexchange). Entities also may include STA-specific concepts such asalerts and the configuration of library connections. The STA GUI, hence,functions to display and, in some cases, to allow editing of theseentities.

Each of these entities may have a set attributes that provideinformation about the entity. The STA user interface module providesvarious screens that display information about these entities. In somecases, various aggregations of these attributes (e.g., total megabytesread by a drive during a day or the average error count of a drive overtime) or counts of events are of interest to a user, and the userinterface may provide ways to display such aggregated values. Some ofthe entities have a hierarchy, and the user interface may provide waysof navigating this hierarchy. This hierarchy is defined in the STA datamodel and is reflected in the GUI. While the STA application may displayindividual entities or sets of entities, many screens will contain datafrom multiple different entities. In database terms, this is a “join”operation between the different entities. For example, a “drive health”display may pick up fields for drives, exchanges, and analytics. In thisdescription, the term “information set” may be used to refer to a set ofrelated attributes. Displaying these information sets constitutes alarge portion of the GUI functionality. Groups of identically structuredinformation sets, such as the drive health information sets for alldrives in a library, are frequently used in the STA GUI.

With regard to a useful GUI structure, the STA GUI provides one or more“windows” or “screens.” Each of the screens may be divided into“panels,” that are each a section of the screen where “components”appear, with components including things like menu items, combo boxes,tables, graphs, and the like (which may also be termed controls,widgets, and the so on). The STA application may show the data in aninformation set in various views. Some views show the attributes of asingle or multiple information sets. Other views show aggregations ofthe attributes from a group of information sets. The aggregations mayalso include simple counts of items that meet specified criteria. Panelsor screens that show these views may also include components that allowselection, sorting, navigation, or other functions.

In some embodiments, the user interface module of the STA applicationprovides at least three basic types of views. First, a “single” view isprovided in the user interface that shows a list of attributes for onesingle information set. This view is a list of named values, with thename/value pairs arranged vertically, for example, but other morecomplex arrangements (e.g., grouping related fields) may also be used.Second, a “multi” view is a table with multiple information sets. Eachrow is one information set and attributes of the information set areshown, for example, in columns. This typically is the same informationshown in the single view but for more than one entity (but, of course,it is possible only one entity may be shown in such a table). Third, an“aggregate” view is provided that may also be a table. In this view,attributes of the information set are used such as for both rows andcolumns and show some aggregation in the cells of the table. Such atable may be thought of as a pivot or crosstab. In practice, variationsof these three types of views are used throughout the STA GUI to displayone or more information sets.

In addition to these three basic views, specialized views may also beprovided such as a dashboard and an overview. A “dashboard” view may beprovided that is a very high level view of everything that the STAapplication “knows” (e.g., collected raw data (in the warehouse and tapesystem model tables), analytics results, summarized data, healthindicators, alerts, and the like). The dashboard view may be thought ofas being a summarized or boiled-down version of the monitoring data. Thedashboard functions to give the user a quick look at their entire tapeinfrastructure. The “overview” view also typically covers the entiretape infrastructure. This view provides additional detail over thatprovided by the dashboard view but may still provide summarizedinformation. This summarized data may be presented in the form ofcharts, lists, tables, or other display components that are useful formeaningfully presenting the data from the STA database. Preferably, theSTA application will be configured to provide a number of differentgraphs or tables that can be shown in the dashboard screen, and a usermay be able to choose the items they want to be shown in the dashboardand overview screens of the user interface.

At this point, it may be useful to describe the STA user interfacefunction with reference to several exemplary screens and views. FIG. 13illustrates a screenshot 1300 of an exemplary GUI that may be generatedby the STA application for display and interaction on a client device(e.g., a monitor of a tape operations manager's workstation or thelike), and the GUI 1300 includes a window or screen 1310 providing adashboard view, as shown with dropdown/menu panel 1320 (with theDashboard view being selected). The dashboard of screen 1310 may be thefirst screen seen by an STA user when they log onto the STA system.

As shown, the dashboard view may include a number of panels providingSTA data at a relatively high level. These may include: (1) a mediapanel 1330 (which may show, in smaller views or subpanels, health ofmedia in the tape infrastructure such as by media type (e.g., use,monitor, action, and unknown indicates may be assigned) and may showtypes of media in library media cells); (2) a drives panel (which mayshow health by drive model, drive models in various library drive bays,and drives requiring the most cleaning per megabyte, or the like); and(3) a libraries panel (which may show health by library model, volume ofdata reads and writes, exchanges for a time period, enters and ejects bycounts over a monitoring time period, or the like). Generally, thesubpanels/views may be used to give a user status of components of tapeinfrastructure (such as status of libraries, media, and drives) and mayshow alerts in some embodiments for various components/portions of atape infrastructure.

FIG. 14 illustrates a screen shot 1400 of the GUI provided by the STAapplication when an overview has been selected by the user for media asshown by the new state of the GUI panel 1320. A panel 1410 is providedthat provides an overview view for media in the tape infrastructuremonitored by the STA application. The panel is shown to include data1430 in graph format (e.g., average read throughput, megabytes written,and average overall throughput) and also data in table form (or in listor multi view) 1450 (e.g., a table showing the following for each volumeserial number: media type, media health, an alert status for a mediaload limit, an exchange start time, a drive type, drive WWNN, exchangeerrors, fault symptom codes, and average overall throughput).

From the screen shown in FIG. 14, a user may choose to drill down or toview a single view for a particular component of the tapeinfrastructure. As shown in FIG. 15 with screen shot 1500 of the GUI,the user has selected a detail or single view for a particular tapemedia. This may provide additional STA data in raw form, in summarizedform, and/or the results of analytics for the media (e.g., a healthstatus or the like). For example, as shown, the panel or view 1510 mayinclude subpanels or smaller views that provide: details for the media(which may include a calculated media health indicator), currentcleaning uses, media activity counts for a particular prior time period,media cell location information, most recent exchange data (which mayinclude exchange errors, a write efficiency indicator, and a mediasuspicion level as well as other analytics results), drive health, andlibrary information.

Instead of selecting an overview view, the GUI may be operated toparticularly retrieve analysis data (e.g., graphics generated based onresults/output of the analytics subsystem) for components of themonitored tape infrastructure. FIG. 16 illustrates a screen shot 1600 ofthe STA GUI after a user has selected from the pull down menu ofdashboard panel 1320 to view analysis data for the drives of the tapeinfrastructure. In this non-limiting example, a panel or view 1610 isprovided with drive analysis data from the STA database provided ingraphical form at 1630 and in list/table form at 1650. This particularexample shows computed or calculated health of drives with the healthshown as being either unknown, use, monitor, or action (with use beinggood health and action being bad operational health).

As can be seen with these screen shots, much of the data captured by theSTA application lends itself well to being displayed graphically. Forexample, a drive health report may show the latest values of drivehealth parameters. The STA tracks a history of these parameters inaddition to the most recent values, and these values may be displayed ina multi view, with various times in the rows of the view. Moreparticularly, this would be a multi view of the drive analytics (ifindividual data points are desired) or drives summaries (if periodicvalues are desired). Since these parameters are numeric, a graph is anatural way to show this data. Further, displaying this data as a graphallows the data for multiple parameters or for multiple drives to bedisplayed on one graph. Graphs may also be used to display the STA datain aggregate views. For example, pie charts and bar charts are goodrepresentations of rows or columns in an aggregate view. Small graphscalled “sparklines” may be display inside multi and single views in theGUI. Sparklines show a graph, typically a line graph in a small size andwithout the usual axes and labels typically shown on larger graphs. Theidea of the sparkline is to give a view of the trend in the parameterrather than a detailed view of the actual parameter values.

The single, multi, and aggregate views may be used for the differententities and information sets. In most cases, the multi and aggregateviews also have selection criteria applied to them. For example, a multiview of drives might use selection criteria to limit this list to allthe drives of a specific type or in a specific library. Various forms ofselection may be provided by the STA user interface, tailored to theitems being selected. For example, time ranges may be controlled withsliders or selections like “last 24 hours” or “last seven days” whilethe choice of drive type may be done using a list of possible choices,each with a check box next to it for example.

The STA GUI may, in some implementations, provide a user withcapabilities to customize views to suit the user's needs. For example,ADF tables or other tools may be used to provide the ability to dosorting by clicking on column headers. The pivot tables used in theaggregate views provide the ability to swap rows and columns. In tables,columns may be hidden, exposed, and reordered. These capabilities areexposed to the STA application users.

The GUI also provides the ability to save the parameters used to defineany view. Once a user has adjusted a view to show the data of interest,the user interface may save the parameters used to produce that view asa custom view or template. The users may give the view a meaningful nameand choose to make the view visible to other users of the STAapplication/system. The saved view or template may include a base view,any selection criteria used for the view, any sorting that has beenapplied, and any column hiding choices. As will be understood, there arequite a large number of potential views that may be displayed by the STAuser interface module. It is likely that a user may be primarilyinterested in a small number or subset of all these available views, andthe user interface module allows them to customize these views tospecifically fit their tape monitoring needs. The STA application will,in some embodiments, provide the ability to assembly a set of viewsand/or panels into a customized screen. A user can select the views tobe displayed on a screen and then save the customized screen layout. Theviews added to a custom screen can be either pre-defined or default STAviews or customized views.

FIG. 17 provides a flow chart of a tape operations monitoring andanalysis method 1700 that may be performed during operations of a datastorage system described herein that includes and uses an STAapplication such as the STA applications shown in FIGS. 1-4. The method1700 starts at 1710 such as with the connection of an appliancepre-loaded with an STA application into a user's data storage system orwith the installation of an STA application onto a server that iscommunicatively linked with a data center (or tape infrastructureincluding one to many tape libraries), with a library host softwarecomponent (in some embodiment, e.g., a mainframe HSC may support the STAor an open side HSC (aka ACSLS) may contribute data to the STA in othercases), and with a user's/monitor's client device (e.g., a computerworkstation, a mobile communication device, or other device forreceiving data from an STA user interface module).

The method 1700 continues at 1720 with the STA application extractingraw data sets from the data sources. The data sources typically willinclude a tape library, and the STA application may be provided directcommunication with the library. A data transport mechanism such as SNMPis used to communicate raw data (e.g., tape mount and dismount records)to the STA application. The host software component (HSC) data also maybe gathered (requested in some cases by a data collector agent onmainframe such as the HSC) and provided to the STA application to allowit to have a more complete set of operational data for each of the tapelibraries (e.g., some of the data from the host software component maynot be found in the tape library data).

At 1730, the STA application uses data loaders to store the raw data,typically with minimal parsing to retrieve useful or desired data, intostaging tables in an STA database (provided in memory on the devicerunning the STA application or otherwise accessible by the STAapplication). At 1770, the method 1700 continues with generating a userinterface (e.g., a browser-based GUI) to the tape monitoring data. Thedata includes the raw facts tables, the analytics tables, and also thesummary tables, and the viewer may use default views or screens or mayreorganize the displayed data or views to create customized screens forviewing the operational data for a particular monitored tapeinfrastructure or data center. The method 1700 may then end at 1790 orcontinue at 1720 (as data is continued to be received/gathered andprocessed by the STA application to update or refresh the STA data and,hence, the GUI/user interface at 1770).

At 1740, the staged raw data is processed by transformers (e.g., SNMPtransformers) to normalize the data for further processing (use by thedata analytics subsystem) and use in generating views of the STA GUI(use by the user interface generation module), and the transformed datais stored in tape system model tables and warehouse tables as discussedin detail previously.

The method 1700 then continues on with the data in these tables ortransformed data being analyzed at 1745 (e.g., algorithms andcomputations being performed using analytics parameters) by the dataanalytics subsystem and then summarized at 1750 (or concurrently withstep 1745. In some cases, the summarization 1750 may be performed topre-compute some information to make the analytics module/processes at1745 more efficient. The analytics 1745 may include computingoperational values such as efficiencies and also includes determiningcurrent health of various components as well as predicting failures ofthese components (e.g., predicting a decline in the operational healthof a drive or a tape media to a point where its use may not be advisedor even possible). The results or output of the steps 1745 and 1750 arealso stored in tables in the STA database. The output of steps 1730-1750may be presented at 1770 to a user via a user interface.

At 1780 (which may occur concurrently with steps 1730-1770), the method1700 also is shown to include determining, with an alert module of theSTA application, whether an alert condition has occurred (e.g., is analert required based on the summarized data, raw data, analyticsoutputs, and alert notification rules tables). If not, the alertcondition monitoring continues at 1780. If yes, the method 1700continues at 1786 with the alert module generating an alert andtransmitting alert messages to a list of recipients, e.g., sending ane-mail message or the like to each addressee in a list provided in thealert notification rules tables of the STA database. The alerts may alsobe presented in the user interface and stored in alert tables in the STAdatabase. After step 1786, the method 1700 may continue at 1780 or endat 1790 (and, also, may concurrently involve steps 1720-1760 as well asstep 1770). In some cases, step 1786 may include opening servicerequests automatically or as part of the alert generation, such as withthe provider of the tape library or the STA module.

The above described invention including the preferred embodiment and thebest mode of the invention known to the inventor at the time of filingis given by illustrative examples only. It will be readily appreciatedthat many deviations may be made from the specific embodiments disclosedin the specification without departing from the spirit and scope of theinvention.

Particularly, the analyzer utilized in the analytics subsystem may takea variety of forms to practice the STA system, and the output of such ananalyzer and corresponding analytics subsystem may vary such as byaltering health indicators and other portions of the user interface,alerts, and messages sent during operation of the STA system. Theanalyzer may implement a method for applying weighted values to failuresand channel reliability indicators for tracking these failures across apopulation of drives and media to determine if a drive or media isfailing or about to fail.

Briefly, such an analytics method may use weighted values and tape driveand media successful accesses and failures tracked across a database,which saves specific information for each drive and tape (medialelement) involved in an exchange. An exchange is the “get” of a tapecartridge from a library slot, loading that media into a tape drive,unloading that media, and the “put” of that media back into a libraryslot. The analytics method may assign weighted values that get added toor subtracted from a suspicion level that may range, for example, from 0to 1. A value of “0” indicates a drive or media is in good health andshould be used while a value of “1” indicates that action should betaken to service a drive or media. Such an algorithm or method allowsthe STA system to identify whether a tape or media needs service and topinpoint which component is experiencing failures or is about to fail.

An issue that has existed since the beginning of tape drive developmentalmost fifty years ago has been how to determine whether a tape drive ora tape cartridge (media component) is at fault in the event of an errorbeing detected. Existing health monitoring techniques generally involvedisplaying detected failures such as by indicating that an exchangefailed when a particular media was mounted on a particular tape drive.However, monitoring personnel would be provided no indication whatsoeverbased on this current status data which of these two components were thecause of the failure.

The analytics methods described herein is useful for indicating theprobable root cause of a detected failure (drive or media has a highassigned suspicion level, for example, and/or via historical dataavailable for a set of past exchanges, such as past 10 to 15 exchangesor the like). Further, the analytics methods include a process foreffectively predicting failure before it occurs in a tape storageinfrastructure through the use of an STA suspicion algorithm, which maybe implemented by the analytics modules/software described throughoutthis description (e.g., by STA application 164 in FIG. 1, by analyticsmodule 346 in FIG. 3, and by analyzer 449 in FIGS. 4 and 11).

Health Gain Gain Value Type Precedence Definition −0.1 GT0 7 Gain Type0, No failure 0.25 GT1 3 Gain Type 1, Failure on subsequent exchangewith the same drive or the same media 0.4 GT2 2 Gain Type 2, Failure onsubsequent exchange with a different drive or media 1 GT3 1 Gain Type 3,Failure with Fatal/Hard Error based on FSC 0.1 GT4 4 Gain Type 4, Thedrive cannot write or read efficiently and minimum amount of data hasbeen transferred (i.e., Gain Type 4 refers to a non-failure case) 0.25GT5 3 Gain Type 5, The first failure in a range of exchanges −0.4 GT6 6Gain Type 6, No failure immediately after a GT3 failure −0.05 GT7 5 GainType 7, Less than the minimum amount of data transferred with no error

In memory accessible by the analytics module, a set of health gainvalues and their definitions may be stored for use in processing the STAsuspicion algorithm for each media and tape drive in a tape storageinfrastructure. In the above table, the first column shows exemplaryhealth gain values that may be assigned to a corresponding set or numberof different gain types shown in the second column. One of the listedgain types is assigned by the STA analytics module for each drive andmedia involved in an exchange. The fourth column of the table providesdefinitions of each of these gain types that may be assigned by theanalytics module.

Further, the analytics module may apply an STA suspicion algorithm ormethod that only applies one health gain value (or HGV) in thecalculation of a current suspicion level value. One technique forchoosing between two or more gain types that may exist after an exchangeis to use a priority or precedence value as shown in column three of thetable. The HGV with the highest precedence is utilized when two or moreare identified after an exchange in a tape library, with 1 being ahighest precedence possible and 5 being the lowest precedence (in thisnon-limiting example as many other numerical and non-numericaltechniques may be used to choose which of two or more HGVs to apply). Inother embodiments, all or a subset of the HGVs may be applied after eachexchange to determine the current suspicion level value (or currentSLV).

The STA suspicion algorithm utilized by the analytics module uses health“gain” values to assign and weigh the effect of reported errors,efficiency, margin, and other data from the tape monitoring operations(discussed in detail above such as with regard to the data collectionand processing steps 1720-1750 of method 1700 of FIG. 17) on the healthof a tape cartridge/media and also on a tape drive. Efficiency generallymeasures a degradation in performance as compared to a perfectlyoperating scenario. The degradation is generally a function of time andcapacity where the exchange is either taking longer to access the dataor is unable to pack the data in the minimum amount of space (or both).Margin generally measures performance vulnerability where performancemay or may not be lost. Margin measures how close the exchange isoperating to failure limits. An exchange could be operating at maximumefficiency but be right on the edge of failure due to a problem eitherwith the tape or the drive. The table provided above defines how theanalytics module assigns HGVs after each exchange, with an exchangegenerally being the act of a library loading, accessing, and unloading atape cartridge into a tape drive.

The gain values may all be equal in some embodiments or, as shown, thegain values (HGVs) are chosen to be weighted values chosen based on theseverity of a single failure or a sequence of failed or successfulexchanges. The STA suspicion algorithm is performed for each media anddrive involved in an exchange to update each component's current SLV(and, note, the HGV tables and/or HGVs may differ between systemcomponents (media and drive)). The analytics module then acts to assignhealth indicators or health levels to each component based on theircurrent SLV, and, as explained below, this is useful for not onlyidentifying components that need immediate attention but also foreffectively predicting that a component such as a tape cartridge mayfail soon and should be replaced prior to such failure (proactiveactions can be indicated by the health indicators rather than onlyreporting failures after the fact). Another significant concept is thatthe analytics module and suspicion algorithm do not only take a snapshotin time but act to cumulate results of past exchanges to determinehealth. Briefly, the current SLV may be calculated by considering apredefined number of most recent exchanges (such as the last 5 to 20 ormore exchanges with the examples below showing use of the last 10exchanges to provide a useful historical or trending perspective ofhealth).

As noted, the HGVs are not equal in the example shown by the table butinstead are based on the severity of a single failure or sequence offailed or successful exchanges. The limits of the calculated current SLVmay be set to be zero (i.e., a range with 0 being a lowest value for thecurrent SLV) up to one (i.e., a range with 1 being a highest value forthe current SLV) such that a suspicion level value cannot be negative orhigher than one in this example, and the term “gain” is used to indicatethat the amount of suspicion that a particular component is the cause ofa problem in an exchange or that the component has or will soon fail(predictive health) is increasing with the most recent exchange (or ifthe gain is neutral or negative the component is determined to be lesssuspicious as being a cause of operating problems).

It should be understood that the range of current SLVs may be nearly anyuseful range defined by lower and upper limits, and the HGVs assigned toeach gain type may be varied to practice the invention. The weighting ofthe HGVs is generally chosen to allow the health to deteriorate rapidlybased on certain failures but to also gradually worsen on repeatedsmaller operating deficiencies or problems and also to gradually recoverupon continued good operations. For example, a tape drive may have itscurrent SLV increased when collected I/O data such as read efficiency isless than an acceptable value with a particular media, and the same tapedrive may have its current SLV reduced back to or toward the lowestvalues (e.g., zero in this case) when no further failures are identifiedfor a number of exchanges with other media (i.e., it was likely themedia and not the tape drive that was the problem in the earlierexchange). Such historical tracking and accumulation of the results ofexchanges has not been used previously to provide health indicators thatprovide a current state of a tape drive or media but also provide usefulpredictive data for maintaining the components of a tape storageinfrastructure.

Turning again to the above-provided table, the first HGV is a gain typeof “0” which corresponds to the processing of the exchange-related datato determine that there was no failure, and, in such a case, the HGV isset to a negative value (e.g., −0.1) so as to allow the component torecover its health (or to have its suspicion reduced as being a rootcause of operational problems). Again, the HGV would be assigned to boththe tape drive and the media involved in the corresponding exchange. Insome embodiments, the suspicion value is not less than zero (e.g., zerois the lower limit on suspicion for a component or piece of media)regardless of how many negative HGVs are assigned in monitored exchangesor transactions.

The second HGV is a gain type of “1” that corresponds to a failure on asubsequent exchange with the same drive or the same media, and the HGVis set to a positive but relatively small value compared to the upperlimit (e.g., 0.25 which is much smaller than the limit of 1.0 in thisexample). In contrast, the third HGV is a gain type of “2” thatcorresponds to failure on a subsequent exchange but with a differentdrive or media. In this case, the HGV is set to a positive butrelatively larger value (e.g., 0.4) because it is more likely that themedia or drive is at fault (more suspicious of being a problem) if itfails on two or more exchanges within a predefined number of pastexchanges (here, 10 exchanges) with differing drives or media ratherthan with the same drive or media (e.g., if a single piece of mediafails on two differing drives within a small number of exchanges it ismore likely to be defective than if it fails on the same drive (whichmay then be more suspicious than the media)).

The fourth HGV is for a gain type of “3” that corresponds with a failurewith a fatal or hard error being determined by the analytics module frominput data (e.g., based on a FSC (fault symptom code) from a tapelibrary) and lookup with the FSC to classify the FSC as a gain typeshown in the table. In this more serious case, the HGV is set to theupper limit for both the drive and the media (e.g., 1.0 when the upperlimit is 1.0). The fifth HGV is for a gain type of “4” that correspondsto the drive not being able to write or read efficiently but at least aminimum amount of data has been successfully transferred. In this lessserious case or less serious operating condition, the eighth HGV is setnearer to the lower limit for both the drive and media (e.g., 0.1 whenthe lower limit is 0 and the upper limit is 1). In this way, the upperlimit may still be reached within the set or number of monitoredexchanges (e.g., 0.1 is equal to 1 divided by the number of monitoredexchanges (i.e., 1/10 exchanges in this example)).

Note, FSCs may be used to determine the type of error that has occurredin an exchange. This ability is not limited to a particular driveprovider but, instead, may be used with nearly any tape drive (e.g.,tape drives provided manufactured or distributed or sold by Oracle, IBM,HP, or the others). For example, error determination algorithms for theSTA module or suspicion algorithm have been created that are driveagnostic (not limited to FSCs or a particular type of exchange data),and the monitored or processed data may be reported by the drive in apublic manner (e.g., not considered proprietary by the tape drivemanufacturer/provider) or it, alternatively, may be proprietary. Inbrief, a useful aspect of the STA module or software product/service isthat it is useful with all or nearly all tape drives (and tapecartridges) and not just with those of one drive or media source.

The sixth HGV is for a gain type of “5” corresponding with adetermination by the STA analytics module that a failure is detected butit is the first failure in the range of monitored exchanges (e.g., firstfailure within the set of 10 most recent exchanges for the media or forthe tape drive). The HGV may be set somewhat higher to indicate thecomponent may have become defective (e.g., a HGV of 0.25 which isgreater than the value for GT4 exchange). The seventh HGV is for a gaintype of “6” corresponding to detection of no failure after a GT3exchange or failure, and the HGV is set to be negative with a relativelyhigh absolute value to allow the component to recover its health orsignificantly lower its suspicion as it operated successfully after afatal or hard error that may have been the fault of the other component(e.g., of the drive when media is being monitored by the analyticsmodule in the present exchange). The eight HGV is for a gain type of “7”corresponding with a determination by the STA analytics module throughprocessing of input data that less than the minimum amount of data wastransferred but without error. An HGV value that allows a small amountof health recovery may be assigned for this condition or type ofexchange result (e.g., an HGV or −0.05 when the range of current SLVs isset to 0 to 1.0).

As discussed above, the suspicion algorithm may only use one (or asmaller number than that available) of the reported exchangeresults/statuses such as one fault or error or reading efficiency perexchange. To this end, the table provided above shows a range ofprecedence values being assigned to each gain type with the more seriousgain types having higher precedence (e.g., 1 is highest precedence inthis example and 7 is the lowest).

As discussed above, the current suspicion level value (SLV) is used toassign a health indicator to each tape drive and media in a storagesystem that is monitored with the STA application. This value iscumulated based on the last 10 (or other number) exchanges completed bythe tape drive or media. With “n” being the current SLV, one embodimentassigns the following four health indicators to the tape systemcomponents (media and tape drives): (1) “Use” when n=0 and no exchangeerror set to 1, 2, or 3; (2) “Monitor” when 0<n<0.80; (3) “Evaluate”when n≧0.80; and (4) “Action” when n=1.0 or Gain Type 3 is detected foran exchange. In this example, four levels or ranges of health areprovided but other embodiments may use fewer or more health indicators,and, in this example, “Use” is the healthiest state and “Action” is theunhealthiest state (e.g., maintenance or replacement needed for thiscomponent because even though it may not yet be associated with a Type 3result it may fail soon based on the prediction of the STA application).A “Monitor” indicator may be used to indicate that some smaller level ofconcern or suspicion is associated with the component, but no immediateaction is required or even recommended by the STA application. Incontrast, the “Evaluate” indicator may be used to indicate thatproactive maintenance or replacement is recommended as the STA analyticsmodule is predicting an upcoming failure because the suspicion level ofthis drive or media has reached an undesirable level (e.g., had 8inefficient reads/writes in last 10 exchanges or had two GT2 results orthe like). In this manner, the analytics module may operate to usehistorical data (exchange data or “performance indicators” or“performance metrics”) to predict future failure or undesirableoperations of a particular component within a tape storage system.

FIG. 18 illustrates a method 1800 for predicting the health of tapedrives and media within a tape storage system. For example, the method1800 may be performed by the STA application 164 in FIG. 1, by analyticsmodule 346 in FIG. 3, and by analyzer 449 in FIGS. 4 and 11, and themethod 1800 may be thought of as explaining in more depth the steps ofmethod 1700 of FIG. 17 (especially step 1745).

The method 1800 begins at 1805 such as with providing an STA applicationon a server or other computer linked to a data center (e.g., a number oftape libraries) and to an appliance used to display a monitoring GUI tomonitoring personnel. At 1810, the method 1800 continues with storing,in memory, analytics parameter values for use in predicting tape driveand media health. For example, the gain type definitions along withhealth gain values for each gain type may be stored in memory accessibleby the STA application (as shown in the table above) Further,definitions of health indicators relative to current suspicion levelvalues (SLVs) may also be stored or revised at step 1810. In some cases,these values may be set to suit a particular data center implementationor customer's/user's needs (e.g., with fewer levels and/or with more orless sensitive trigger points between a healthy (Use or Monitor) to anunhealthy component (Evaluate or Action)). Also, a lookup table(s) maybe stored for determining which gain type should be associated with eachpiece of exchange data such as an FSC to Gain Type lookup table thatallows failures, read/write rates, and the like to be converted to gaintypes associated with various HGVs.

The method 1800 then continues at 1820 with providing a data store suchas a database in memory accessible by the STA application. This datastore is used to store a history of exchange data for each tape driveand media (e.g., tape cartridge) in a monitored tape storage system.Particularly, a record may be provided for each system component thattracks the results of a predefined number of prior exchanges includingthe HGVs assigned to the component for each of those exchanges (e.g.,for the past 10 exchanges or some other number). This historical data isuseful for later determining a current suspicion level value (SLV) upona next exchange. The record may also include the current SLV and acurrently assigned health indicator for that component (e.g., use,monitor, evaluate, action, or other useful health indicators determinedbased on current SLVs).

The health predicting and monitoring method 1800 continues at 1830 withdetermining whether additional exchange data has been received from atape storage system (e.g., from a tape library). If not, the method 1800continues until a next data set or message (e.g., an FSC) is received bythe STA application. If an exchange has occurred and corresponding datareceived at 1830, the method 1800 continues at 1840 with classifying theexchange with a gain type for each component (e.g., drive, media, and soon) involved in the exchange. This classification may involve the STAapplication performing a lookup with an FSC to determine a correspondinggain type. Such classification may also involve using performancemetrics such as read/write efficiencies to determine whether a minimumread/write amount is achieved in the exchange. Further, the classifyingat 1840 may involve the STA application retrieving data from theexchange history database for the drive or media such as to determinewhether this was the first failure within the monitored set of exchanges(first failure in the past 10 exchanges), whether the failure occurredwith a different media or drive after an earlier failure within themonitored set of exchanges, and so on to satisfy the gain typedefinitions stored in memory in step 1810 (e.g., as shown in the tableabove).

Once the exchange data has been converted to gain types for eachcomponent, the method 1800 continues at 1850 with the STA applicationretrieving/determining the health gain value (HGV) for the gain typewith the highest precedence for the monitored exchange. At 1860, thecurrent SLV is calculated by the STA analytics module. In some cases,this may simply involve adding the HGV from step 1850 to the previousSLV for the drive and for the media. In other cases, though, step 1860involves summing the prior HGVs assigned to each of the exchanges in theset of monitored exchanges (e.g., the prior 10 exchanges), with one oldexchange being dropped from the summed total once the number ofmonitored exchanges is exceeded (e.g., when 11 exchanges have occurredwhen 10 exchanges are tracked/monitored the oldest exchange is no longerused in the calculation of the current SLV).

At 1870, the method 1800 continues with storing in the health monitoringdatabase the current SLV for each component (e.g., drive and media)involved in the exchange. At 1880, the STA application acts to determinethe health indicator to use to represent the current health of the driveand the media, and the health indicators are stored in the database,too. For example, the HGV may cause the health to change such that newhealth indicator is assigned to the drive or media such as a change from“Use” to “Monitor” or from “Monitor” to “Evaluate” and so on. The healthmay improve or it may degrade during monitoring, and this is reflectedin near real time with the STA application and performance of method1800. At step 1890, the method 1800 continues with updating the GUI toshow the new health indicator (and, in some cases, the SLV) and/or withissuing alerts based on the updated health indicator such as when thehealth changes to “Evaluate” and “Action” alerts may be transmitted tomonitoring personnel. The method 1800 may continue at 1830 withprocessing of additional exchange data or end at 1896.

As shown with the exemplary method 1800, the STA application acts at theend of each exchange to add a HGV to the previously determined set ofHGVs for both a tape drive and a tape cartridge involved in theexchange. The current SLV, in the example provided by the above table,either increases toward the upper limit or decreases toward the lowerlimit. The suspicion algorithm may use values that generally increase ordecrease the SLV slowly, with only a fatal or hard error failure or GainType 3 resulting in immediate reaching of the upper limit and an“Action” health indicator. Testing with the suspicion algorithm hasindicated that such a gradual change in the health of a drive or a tapecartridge is more useful in correctly identifying a problematic or rootcause of a failure and determining an ongoing operational problem. Thesuspicion algorithm uses the database with a history of previousexchanges for each component (drive or media) that builds upon pastfailures or successful exchanges to determine the current health of thecomponent and also to predict a likely failure of a component (e.g.,those components marked as “Evaluate” in the above health indicatorexamples).

In the following example, a drive or media is monitored through 10exchanges (shown in the columns of the table), and the HGV for thepresent exchange is shown at the bottom of each column along with thecurrent SLV for the drive or media. In the example, the current SLV isused to indicate the health of either a tape cartridge (media) or a tapedrive based on the last ten exchanges, and this current SLV may beconverted into a health indicator as discussed above by the STAapplication. This example shows alternating successful exchanges (GT0)with negative exchanges (but not hard/fatal errors) associated with GT1and GT2 gains that cause the suspicion level to gradually increase overtime or through a number of exchanges.

Exchange GT0, GT1 or GT2 result every other exchange 1 0 1 0 2 0 2 0 2 02 2 0 0 1 0 2 0 2 0 2 0 3 0 0 0 1 0 2 0 2 0 2 4 0 0 0 0 1 0 2 0 2 0 5 00 0 0 0 1 0 2 0 2 6 0 0 0 0 0 0 1 0 2 0 7 0 0 0 0 0 0 0 1 0 2 8 0 0 0 00 0 0 0 1 0 9 0 0 0 0 0 0 0 0 0 1 10  0 0 0 0 0 0 0 0 0 0 SLV 0.00 0.250.15 0.55 0.45 0.85 0.75 1.00 0.90 1.00 HGV −0.1 0.25 −0.1 0.4 −0.1 0.4−0.1 0.4 −0.1 0.4

The above table shows that in a first exchange, the gain type isidentified as GT0 such as may be the case if there is no failure orunacceptable performance metrics detected by the STA application basedon processing of received exchange data. This causes a HGV of −0.1 to beapplied, and the SLV remains at zero as this is the lower limit in thisexemplary implementation of the suspicion algorithm. In the nextmonitored exchange for this drive or media, the gain type is identifiedas GT1, which corresponds to a HGV of 0.25 and with application of thisHGV the current SLV becomes 0.25. This would result in the healthindicator being changed from “Use” to “Monitor” for this drive or media.In a next or third monitored exchange, the gain type is identified asGT0 such that a −0.1 HGV is applied to reduce the current SLV to 0.15.This does not cause the health indicator to be changed, but the healthmonitoring database is updated to reflect the current SLV and to showall the monitored exchange data.

The monitoring continues with a fourth exchange that provides a gaintype of GT2, and this is converted into a HGV of 0.4 that is added tothe previous SLV. The current SLV is increased to 0.55, which in thisexample maintains the “Monitor” health status or indicator for the mediaor drive. In a fifth exchange, the exchange data is processed to providea gain type of GT0, and this corresponds to a HGV of −0.1 such that thecurrent SLV is reduced to 0.45 (e.g., the health improves or suspicionregarding the component is reduced). The health indicator is againunchanged. With a sixth exchange, a GT2 is received such that the HGV is0.4. Adding this to the previous SLV (or summing all 10 recentexchange-based HGVs) produces a current SLV of 0.85. Hence, thesuspicion level has crossed another health boundary or trigger point,and the STA application changes the health indicator to “Evaluate” forthe drive or media, and, if appropriate, an alert may be transmitted tomonitoring personnel or a GUI updated to reflect this change in healthstatus. In this state, the STA application is effectively predictingthat the component is likely to fail in the future unless maintenance isperformed or the component is replaced.

In the seventh exchange, the HGV is again determined to be −0.1 with nofailure being noted in the exchange. The current SLV improves to 0.75such that a corresponding health indicator also improves to only“Monitor.” However, in an eighth exchange in the library, the media ortape has a failure on a subsequent exchange with a different drive ormedia (GT2), which is associated with a HGV of 0.4. The STA applicationadds or sums this with other HGV values in the 10 exchanges such thatthe maximum level is reached (cannot exceed 1.0 in this example). Hence,the STA application may change the health indicator based on this newSLV to that of “Action” from “Monitor,” and an alert may be transmittedto monitoring personnel and the monitoring GUI updated to reflect thataction should be taken as the component is very likely to fail soonand/or is operating poorly based on the high suspicion level that hasbeen produced by repeated poor performance and not a single fault orerror.

With a next or ninth exchange, the HGV is again −0.1, which when addedinto the SLV brings the current SLV down to 0.9 or less than the“Action” health indicator or status into the “Evaluate” range. The alertmay be downgraded at this time. With the tenth exchange, the HGV isagain positive with a GT2 providing a 0.4 HGV such that the current SLVrises back up to 1.0 or the maximum amount, and the STA applicationagain may issue an alert indicating the health indicator is again at“Action” rather than merely monitor. While this component has notexperienced a failure of the GT3 type, it is likely to fail soon andshould be maintained/replaced or operations should be controlled toreduce use of this component in future exchanges (again, a predictiveindication is being provided and not a mere indication of present statusof the component, and this prediction is based on historical exchangedata that may include performance metrics or indicators).

In this example, it can be seen that the result of the previous exchange(i.e., a gain type and its associated HGV) moves down as the nextexchange is included in the set of monitored exchanges (10 in thisexample). The gain type is shown for each exchange for the “1” exchangerow or row associated with the most recent exchange in the set, and witha next exchange (movement to the right in the table to a nextcolumn/exchange) the oldest or 10^(th) exchange gain type (andassociated HGV) drops off or is now excluded from the sum defining thecurrent SLV for the media or drive. In this example, the suspicion levelvalue (SLV) slowly increases over a number of exchanges from “Use” to“Monitor” to “Evaluate” and then “Action,” showing that the predictionmethod is useful for tracking suspicious behavior over a number ofexchanges to predict future behavior (failure or continued success)and/or identify a root cause between a drive and mounted media in afailure scenario.

The STA application may utilize a relatively simple algorithm that canbe easily modified as the interaction of drives and media becomes betterunderstood to better predict health of media and/or drives. For example,increasing, decreasing or adding new gain values and precedence valuesmay be performed to achieve more accurate or desirable results inpredicting future operational performance of media and drives. In someembodiments, such modifications may be done automatically by the STAapplication to react to actual failures of components such as toincrease gain values if components that are only listed as monitor failat an undesirably high rate so that components more quickly reach the“Evaluate” and “Action” levels. In other embodiments, intelligence maybe provided that tunes the gain values within each system to matchcharacteristics of the particular drives and media being used within atape storage system. Additionally or instead of such automated adaptedtuning, manual tuning may be performed by a user or monitoring personnelto adjust the predictions made by the STA application. For example, acustomer may indicate that they want a highly sensitive system with manyfewer actual failures and replacement/maintenance prior to failure beingpreferred. In such a case, the HGV values shown above may be increasedand/or the HGV values associated with success or recovering healthreduced in magnitude.

With the above example provided in tabular for and explained in detail,it may be useful to describe several other operational conditions thatmay be monitored with an analytics module of an STA application toreport a health indicator and predict future operational status of atape drive or media used in a tape library or tape storage system.

An exchange history may indicate that a drive fails on every load ofmedia, and, interestingly, the analytics module described herein acts topredict failure or to at least identify that action should be taken forthis drive (or could be for media, too). A first failure in a range ofmonitored exchanges (e.g., past 10 exchanges) will generate a GT5 (GainType 5) that has an HGV of 0.25 such that the current SLV is increasedto 0.25. The next exchange generates a GT2 (Gain Type 2) that has an HGVof 0.4 (e.g., a higher gain value because different media being loaded(or different drive receiving the same media)), and the current SLVjumps up to 0.65. One more exchange again generates a GT2 such that theSLV now exceeds 1.0 or the upper limit, and the health indicator movesfrom Use to Monitor to Action in three exchanges. This may also cause analert to be issued for this drive (or media) even though a fatal or harderror failure has not yet been identified such that the actionrecommended may be thought of as predictive.

Another exchange history may show that a drive (or media) fails on twoof three loads. In this case, a first failure in a range of monitoredexchanges causes the STA application to generate a GT5 with an HGV of0.25, and the current SLV is set equal to this value. A next exchangeproduces a GT2 as a different media (or drive) also produces a failure,and the current SLV is increased to 0.65. However, a third exchange issuccessful such that a GT0 is issued for the exchange with an HGV of−0.1 such that the STA application reduces the current SLV down to 0.55as the suspicion decreases with a successful load. Next exchange,though, the exchange data (e.g., an FSC) indicates that a GT2 againshould be issued due to a failure with another different media, and thecurrent SLV is increased up to 0.95. The next exchange also produces aGT2 such that the current SLV moves up to the limit, and in the last twostates, the health indicator moves from “Evaluate” to “Action” for thedrive. Hence, intermittent failures or reduced performance of a drive ora media may still produce Evaluate and/or Action health indicators ashistorical performance metrics/indicators are considered by theanalytics module of the present STA application (in contrast to priortechniques that typically only reported data and present status so adevice would be as healthy as the last exchange not a cumulativeanalysis).

Another drive may fail on every other load as shown by its exchange data(FSCs from a tape library). In such a case, the STA application willfirst identify a GT5 and then alternate between GT0 and GT2 for eachexchange. In this operating pattern, the drive (or media) will slowlyaccumulate suspicion (or decreased health as shown by changing healthindicators), and it may take seven exchanges in such a pattern to reachthe upper limit and an “Action” health indicator. Similarly, if a drivefails on every third load, the drive will eventually have a current SLVthat corresponds with an “Action” health indicator (e.g., after thirteenexchanges the upper limit is reached). However, a more intermittentfailing drive or media that fails only every fourth, fifth, or moreloads may only rise to the “Monitor” health indicator (or may take muchlonger to reach “Evaluate” and “Action”) as the associated SLV recoversto lower levels with successful loads.

In other cases, it is interesting that if a drive (or media) only failswith a particular media (or drive), the current SLV may never raise highenough to cause the drive (or media) to be identified as requiringevaluation or action. This is typically desirable as such behaviorindicates that it is the loaded media (or drive) that is the problem andnot the component being monitored by the STA application. However, theSTA application and its analytics module act to store records for bothdrives and media in a tape library or tape storage system. As a result,the suspicious media (or drive) causing all the failures will have itscurrent SLV move up to higher values with issuance of GT2 and 0.4 HGVs,and this will cause the health indicator for such media (or drive) to bechanged to “Evaluate” or “Action” and alerts being issued (ifapplicable).

Many other examples of the use of the analytics module will be apparentto one skilled in the art, and it is believed with the above examplesuse of the suspicion algorithm for each of these various operatingconditions will be well understood. Further, it will now be betterunderstood why and how it may be useful to tune the values of the HGVsassociated with the various gain types (or exchange performance results)to achieve more desirable (more accurate or the like) predictions oftape drive or media health.

In some cases, media is by default considered to be more likely to failor be suspicious. In such cases, the table shown above with HGVs forassigned gain types is modified for drives by increasing the HGVs suchthat a media may be assigned an “Evaluate” and “Action” health indicator(or health enumerator) more quickly than a drive having the same gaintypes. For example, each value may be increased by a percentage (such asby 10 to 25 percent) or be increased by 0.1 when the range is 0 to 1between “Use” and “Action” as shown in the examples (which are, ofcourse, not limiting but only considered representative of the describedconcepts).

Hence, some preferred embodiments may treat media and drive (or othersystem components) differently even though both are involved in theexchanges of the tape library. This may be desirable due to the lowercost and ease of replacement of media when compared with tape drives.The records of the tape and media are updated independently throughoutthe STA application monitoring, and the STA application is effective forassociating pairs of drives and media involved in each exchange. Thisallows the STA application to identify whether the drive or theremovable media is more likely to have been a root cause of a failure.

As discussed above, the exchange data provided by the tape storagesystem may include FSCs from software provided on drives or the like. Inother words, the FSCs are one way in which drives report failures andother results of exchanges. FSC lookup tables may be generated andstored in memory to allow the STA analytics module to quickly retrieve aparameter or defined exchange result that can then be converted into again type and its associated HGV. In one embodiment, an FSC lookup tablemay be created for each type of drive and/or media present in amonitored library, and each of the FSC values may be placed within acategory or “bucket.” Then, these categories of FSCs can be associatedwith a gain type for use in the suspicion calculations.

For example, a tape drive may have an FSC lookup table associated withit that includes categories for exchange results such as fatal error(e.g., a reactive or failure indicator rather than a performance metricuseful in predicting future behavior or health), write error, mediaerror, read error, and unload error. Each FSC number or a range of FSCvalues may be placed in each of these categories or buckets, and eachtype of drive or media may have separate FSC lookup tables used by theanalytics module to determine gain types to assign at the end of eachexchange.

In addition to use of FSCs from tape drives, the analytics module of theSTA application may use exchange data to identify or calculatepredictive performance indicators or metrics. Then, these performanceindicators may be used to assign a particular gain type as shown in thetable above to each exchange. For example, it may be useful to determinewhether an exchange produced less than desired efficiencies in readingor writing for use as a performance metric that may be used in thesuspicion level calculation. Reading may be considered marginal if toomuch error correction beyond a preset limit or threshold is needed torecover the accessible data. Writing may be considered inefficient ifthe time or space needed to store the data on tape is greater than apreset limit or threshold. Further, read or write inefficienciesmeasurements may be weighted by the size of the exchange (e.g., the dataaccessed or transferred is less than a preset limit or threshold). Thisprevents normal data access overhead (that may dominate a smallexchange) or relatively small exchanges with relatively minor loss inperformance from being treated equally with the performance of nominalor large data exchanges. When these thresholds are not breached in anexchange, the exchange may be considered successful and, in the aboveexamples, a GT0 may be assigned such that suspicion decreases for thedrive and media. However, if the threshold is not met or exceeded, a GT4or other gain type may be assigned that increases the suspicion levelfor the drive and media involved in the exchange. Hence, performanceefficiency (or other performance indicator or metric) may be used by theanalytics module to determine health of a drive or media rather thanonly relying upon reactive or failure-type exchange data.

For media and drives, it may be useful to process the exchange data todetermine performance metrics such as: exchange elapsed time, exchangemount time, time spent in read/write, exchange read throughput, exchangewrite throughput, exchange I/O throughput, exchange read ratio, exchangewrite ratio, exchange I/O ratio, exchange mount read throughput, andexchange mount write throughput. All or a subset of these metrics maythen be used to determine which gain type to assign to an exchange suchas by first determining whether these are marginal or inefficientexchanges (as discussed above). Further, once this data is calculated,it may be stored for both the drive and media associated with theexchange such that a historical record is provided for the tape storagesystem for each of its components. This data may be kept for numerousexchanges or it may only be maintained for a predefined number ofmonitored exchanges (e.g., last 5 to 20 exchanges or the like with 10exchanges shown in the examples provided).

Beyond the analytics described above with regard to FIG. 18, it may bevery useful and desirable for the analytics performed by the STAapplication to include media and drive validation (MDV) for tapelibraries of a data center. For example, the MDV functions and methodsdescribed below may be performed by the STA application 164 in FIG. 1,by analytics module 346 in FIG. 3, and by analyzer 449 in FIGS. 4 and11, and the methods may be thought of as explaining in more depth thesteps of method 1700 of FIG. 17 (especially step 1745).

Media and drive validation (MDV) can be thought of as a “value add” tothe STA application (e.g., adding an MDV module to the analytics modulesignificantly enhances the information and services provided to a userof the STA application). The MDV module and methods, as will becomeclear, utilize a validation drive(s) and validation tapes (or tapecartridges) within a tape storage library (or libraries of a datacenter) along with a suspicion algorithm to perform drive and/or mediavalidation. MDV is a “value add” because it comes closer to providingbehind-the-scenes, total tape management.

MDV leverages unique metrics supplied by the tape drives during theiroperation within a library (drive data collected by the STA as discussedabove). The STA application without an MDV module and its particularsuspicion algorithms (e.g., the method of FIG. 18) relies on randomdrive and tape matings. Hence, tape “validation” or health monitoringoccurs over varying amounts of time in such a non-MDV modulearrangement, and a tape cartridge (or media) may never get a goodassessment opportunity with such random use by drives of a tape library.In contrast, use of the MDV module and its corresponding MDV methodsaccelerates the assessment opportunity by verifying a tape cartridge orpiece of media with a known qualifying tape drive. For example, the MDVmethod may involve re-validating a tape drive (e.g., with a “gold tape”or previously validated tape) to double check whether or not aparticular tape is in need of special deposition (e.g., copy, replace,scratch pool, or the like) or whether the recently read/written tape(s)may be poorly performing/suspect media.

As a caveat, though, it should be remembered that the MDV module/methoddoes utilize one or more captive drives in a library (or libraries) anduses a known good data recording on a tape (e.g., an STA customer's owndata recorded on a tape may be used as “known good data” during the MDVmethod). These items are provided by the library and its controls sincethe STA application does not physically place drives in pools, but, insome cases, the STA application may recommend drives for use in thepools (described below) such as by using analytics of the STAapplication to provide pre-qualification of drives.

In other words, to perform validation, the MDV module and its validationmethods has several special needs or desirable operating parameters.First, validation of a tape or media is performed using a qualifyingdrive or “the gold drive.” The qualifying or gold drive is configured toprovide a calibrated tool to judge or measure quality of data on a tape,and the label “gold” or “qualifying” is applied to a drive if it passesstricter requirements than applied to other drives (e.g., other normaloperating limits). For example, the qualifying drive may pass a tighterread quality index (RQI), with RQI being useful as it is expected that adrive with a higher RQI will also pass stricter requirements (e.g.,other drive performance metrics likely will follow RQI).

Second, validation of a tape drive may be performed using a qualifyingtape or “the DQ tape” (where “DQ” stands for drive qualification). Thequalifying or DQ tape preferably is selected by the MDV module and itsmethods dues to its very good performance with most any variation of“good” drives (previously and presently validated drives). Also, thequalifying or DQ tape may be required by the MDV module and its methodsto pass stricter requirements than applied to other tapes (e.g.,requirements or metrics that are tighter or more restrictive than normaloperation limits for a typical tape cartridge or piece of media in alibrary).

Third, the MDV methods typically call for the qualifying drive to be inthe larger STA pool (e.g., available for normal operations of a tapelibrary). As a result, the suspicion algorithm utilized in the analyticsdescribed with reference to FIG. 18 may provide skewed results due tothe MDV-specific uses for the qualifying or gold drive. For example,testing of tapes that are suspected of poor health or low performancemay skew the health indicators for the drive (e.g., appears that thedrive is poorly operating due to the higher number of failedreads/writes or the like). To address this issue, the MDV module and itsmethods may use a special or MDV suspicion algorithm to compensate forthe use with numerous bad media/tapes. This is desirable becauseincreased bad media matings may cause the drive to appear suspect, butit should be understood that increased bad media matings may actuallycause the drive to degrade over time (e.g., much faster than otherdrives that work with poor tapes much less frequently over the course ofnormal operations of a tape library).

The STA application may be configured to provide a list of drives andtapes to the MDV module that can be used as a set of candidate tapedrives and tapes for MDV. This list of drives and tapes may be selectedby the STA application based on operating/measured/determined operatingparameters such as normalized RQI, tape capacity, and the like. To feedMDV initialization, a customer or an automated process of the MDV modulemay select 1 or 2 drives from this set of candidates or from the drivesoperating in a library and a set of tapes from the set of candidates orthose available in the library. The MDV initialization procedure thenacts to find the desired drive(s) and tapes to perform customer tapeverification. The STA customer or user may, in some cases, be able toset one or more tapes aside as not being used for MDV, and, in suchcases, it may be useful to provide tapes used exclusively for MDV in thetape library (e.g., media with an ability to write a minimum of 2 wrapsof data on the tapes to be used exclusively for MDV).

With regard to drive qualification (DQ) tape creation, there are anumber of different options or processes that may be followed topractice the MDV module and methods of the present description. First,the STA application (e.g., an MDV module or other program/routine) mayact to select a set of candidate tapes from the tapes (i.e., customertapes) in a library. These candidates may be selected randomly or basedon one or more operating criteria for tapes. Interestingly, in this way,the MDV module uses existing customer data as part of the DQ tapecreation process, and it does not require writing of preselected dataonto a tape.

In a second process, DQ tape creation may involve the customer orlibrary manager creating or selecting a DQ tape from a data path with:second back-up of non-sensitive data, duplicate back-up tapes; or aprogram running on the customer's host that writes to a selected tape.In a third process, DQ tape creation may involve invoking a new functionto create a DQ tape via a control path from a predefined set of tools(e.g., the STA application or the like).

FIG. 19 provides three graphs 1910, 1920, and 1930 that providerepresentations of the use of read margin measurements in performance ofvalidation or verification of operation of drives and tapes by a MDVmodule or as part of a MDV method. The read quality index (RQI) isdetermined based on a comparison of read margin (provided on the Y-axisof the graphs 1910, 1920, and 1930) with a quantity of reads (providedon the X-axis of the graphs 1910, 1920, and 1930), e.g., provides databased on mating of a drive and a tape. As shown at the right edge of thegraph 1930, limits in the RQI value may be selected as part of the MDVmethod that define an allowable depth of degradation (or RQI degradelevels) that are acceptable for pools or select types of tapes and/ordrives within a library managed by an STA application with an MDV moduleprovides as part of its analytics.

As shown at 1912 in graph 1910, an RQI limit may be set (e.g., at adepth of degradation in read margin of 25 percent or the like) thatseparates the gold tapes and gold drives as shown at 1914 from the othertapes and drives as shown at 1918 (the non-gold tapes and drives). Thelimit 1912 may be relatively strict or tight allowing for only arelative small amount of degradation in the read margin for the tapesand drives to be used as DQ or gold tapes and drives. In this way, theDQ tapes and drives can be certified by MDV module as being equal orbetter than customer tapes that were input to the MDV module.

In contrast, as shown at 1922 of graph 1920, a lesser RQI limit may beset (e.g., at a depth of degradation in read margin of about 50 percentor the like) may be set to define which tapes and drives may bere-certified as gold, with area 1924 of graph 1920 showing there-certified gold drives and tapes and area 1928 showing those that areconsidered “degraded” in this RQI analysis or portion of theverification by an MDV method. Re-certification of gold drives, forexample, may have an increased margin from when initially certified, andsome variability may be expected in the RQI values obtained. As shown at1932 in graph 1930, an even lower RQI limit may be set for otherverification processes (e.g., allowing up to 75 percent degradation inthe read margin). Area 1934 shows acceptably performing tapes/driveswhile area 1936 shows tapes/drives that are considered degraded and area1938 shows tapes/drives that are below the limit 1932 but not yetconsidered degraded due to the lower quantity of reads in input datafrom the STA application. Generally, the tapes/drives that areconsidered degraded as shown in area 1936 are unsafe for use but maystill be working. Customer tape and drive limit 1932 is setconservatively to minimize or at least reduce false positives.

At this point, it may be useful to provide one implementation or workingexample for the use of an MDV module and an MDV method in a librarymonitored/managed with an STA application. A gold or DQ drive may beselected from a group of candidates as described above. For example, thegold drive may have been previously qualified to be statistically betterthan most drives by meeting strict requirements (e.g., shown to have anRQI falling in the area 1914 of graph 1910 in FIG. 19). In this regard,a customer or user of an STA application may be requested to provideinput indicating a selection of one or more drives to be qualified forgold status. In some cases, the customer/user may only be able to freeup one drive at a time for such qualification.

Next, the gold drive may be used to determine if a suspect (degraded)tape is actually bad or marginal. Hence, the MDV module of the STAapplication provides the customer with media validation to testquestionable tapes, which may be specified by the user, may beidentified or recommended by the STA application (e.g., based on ahealth indicator or the like), or may be selected automatically inanother manner by the STA application (e.g., validate particular tapesor volumes on a predefined time schedule such as once a day, once aweek, once a month, or the like). Further, a gold drive may bere-verified, such as when a failure occurs, e.g., through RQI analysiswith one or more DQ tapes as shown with graph 1920 of FIG. 19. A golddrive may become marginal over time (e.g., due to its heavier thannormal use with degraded or suspect media), and the re-verificationprocess or step is useful to reduce false or early disposition of goodcustomer tape (e.g., a marginal gold/DQ drive providing lower RQIvalues) and/or drives (e.g., a marginal drive may be re-certified forcontinued use as a gold drive).

FIG. 20 illustrates a process 2000 for initializing a site such as acustomer's data center or library for MDV with an MDV module of thepresent description. MDV initialization 2000 is used to establish one ormore DQ or gold drives, a DQ or gold tapes, and a DQ tape pool. Theinitialization 2000 typically starts with providing or loading an STAapplication (with an MDV module in its analytics module/program) on aserver or other computer linked to a data center (e.g., a number of tapelibraries) and to an appliance used to display a monitoring GUI tomonitoring personnel.

At 2010, the STA application may define or recommend a set of tapes foruse in the MDV process, and the customer/user of the STA application mayselect this set of STA-approved tapes (e.g., tapes with a particularrange of health indicators or with historical operating parameters suchas RQIs). Alternatively, the customer/STA user may make at 2014 tapecopies that are used to feed the MDV initialization process 2000. Thetapes from step 2010 or 2014 are used to define or establish a tape testpool 2020 within one or more tape storage libraries. At 2040, the STAapplication or a customer/STA user provides input selecting one or moredrives in the library to be partitioned for MDV (or by the MDV module tovalidate tapes), and the selected drive or drives are partitioned at2050.

At 2030, the MDV initialization 2000 continues with the MDV modulecausing each tape in the test pool 2020 to be read on one of and morepreferably all of the drives in the set of partitioned drives 2050.Note, due to possible tape and drive interaction, several tapespreferably should pass on the drive that becomes the gold drive, withthe specific number of tapes in pool 2020 and number of drivespartitioned at 2050 being user-selectable/definable parameters of theinitialization 2000. The MDV module uses the data from reading 2030 toselect at 2060 one or more gold drives, e.g., one or more drives mayqualify for gold status at a predefined operating parameter limit (e.g.,an RQI over a limit such 75 percent or the like (or less than about 25percent read margin degradation)). In some cases, the drives may beranked and the drive(s) that ran the most tapes in the best (higherRQIs) is chosen as the gold or DQ drive at 2060.

The MDV module further uses the data from reading operations at 2030 toselect at 2066 one (or more) tape as the gold tape (e.g., a tape with anRQI of greater than 75 percent (or with less than 25 percent read margindegradation)). Further, the MDV module acts at 2070 to use establish adrive qualified (DQ) tape pool 2070, such as by tagging each tap thathas an RQI or other reading-based parameter meeting a predefined limit(e.g., an RQI greater than about 50 percent). The initialization 2000ends at 2080, and the resources including a gold tape, one or more DQtapes (also may be known as the DQ tape pool), and one or more golddrives are made available for customer use, e.g., the gold drives areready for use in validating tapes and the gold tape and DQ tape pool areready for use in re-certifying gold drives.

FIG. 21 illustrates a validation or testing method 2100 performed by theMDV module after initialization 2000 as shown in FIG. 20. At 2110, anevent occurs that indicates that it may be appropriate to test atape/media. For example, the STA application may indicate a degraded orpermanent error event with regard to a tape in a customer's library, andsuch an event may be present via an STA GUI to the customer/STA user orvia an alert that the tape should be validated using MDV. In othercases, step 2110 may involve the customer/STA user selecting one or moretapes for performing routine tape validation such as when thecustomer/STA user receives new tapes that are inserted into a library itmay be useful to validate these tapes prior to use.

At 2120, the testing/validation 2100 continues with the MDV module usinga gold drive to test/validate a tape. For example, the gold drive havebeen certified with a particular RQI such as above 50 percent or morepreferably above 75 percent (e.g., less than about 25 percent readmargin degradation). Step 2120 may involve using another routine to reada potentially degraded tape while in the gold drive (e.g., VolStatavailable from Oracle may be run on the selected tape), with this tapenow being referred to as the “target tape” for MDV or by the MDV module.

At 2150, the MDV module may validate the tape such as when no permanentread error is detected and the RQI is greater than a predefinedacceptable level for a normal/typical tape (not a gold tape) such as anRQI of greater than or equal to (or greater than about) 25 percent. Thethreshold or limit may be adjustable by the customer/STA user such as toa high threshold (e.g., 75 percent or higher), a middle or intermediatethreshold (e.g., 40 to 75 percent with 50 percent shown in FIG. 21), anda lower threshold (e.g., 0 to 40 percent with 25 percent being a usefullower threshold when three thresholds are made available via STA butnearly any number of threshold values may be used at step 2150 toidentify a validated or “good” tape for use in a customer library.

If either of these validation criteria is not satisfied, the MDV moduleat 2130 may determine that the target tape has failed validation (orMDV). Step 2130 may further include testing the gold drive that was usedin the MDV/testing to fail the target tape so as to verify that thisdrive still qualifies as a gold or verification drive. If the drivefails re-certification (see FIG. 22), a new gold drive is identified andsteps 2120 and 2130 are repeated. If the drive is still good asdetermined at 2130, it is assumed that the target tape is as bad as thereading/testing at 2120 indicated. This “bad” tape may then be marked asdegraded to block its continued use and/or to indicate it should beremoved/replaced.

FIG. 22 illustrates a method 2200 that is performed by the STAapplication or by the MDV module of the STA analytics upon a target tapefailing validation (e.g., failing the testing of method 2100 of FIG.21). The method 2200 is useful for determining whether the gold/DQ drivethat was used to test the failed target tape is still validatingcapable. At 2210, the method 2200 includes selecting a DQ tape from theDQ tape pool (e.g., tape pool established at 2070 in initializationmethod 2000 of FIG. 20), and this selection is typically done randomlyby the MDV module but may also be done based on some criteria. Thesetapes typically have an operating parameter above some preset limit suchas an RQI equal to or greater than 50 percent or the like.

At 2220, the method 2200 continues with a statistical gathering toolbeing run on the DQ tape in the gold drive that was used during thevalidation/testing of the failed target tape. The result may be providedsimply as a pass or fail in some implementations of method 2200. If theDQ tape also fails on the gold drive at 2220, the method 2200 continuesat 2230 with identifying the gold drive as now being suspect. This golddrive may be re-qualified or re-certified prior to its continued use asa gold drive (see FIG. 23 and method 2300), and any decision as to thedisposition of the “failed” target tape from method 2100 may be put onhold until completion of re-certifying of the gold drive. If the DQ tapepasses the statistical analysis at 2220 (RQI over a preset limit) on thegold drive, the method 2200 continues at 2250 where the failure of thetarget tape is confirmed. The failed target tape may now be marked oridentified by the MDV module for disposition (e.g., marked for nofurther customer use in the library and eventual removal from thelibrary).

FIG. 23 illustrates a method 2300 for re-certifying or re-qualifying agold drive that fails at step 2230 of method 2200 of FIG. 22. Again, themethod 2300 typically is fully or at least partially carried out by theSTA application with its MDV module running as part of STA analytics (asis the case with methods 2000, 2100, and 2200). Method 2300 is initiatedwhen a gold drive fails and may include selecting the same DQ tape fromthe DQ tape pool as was used in the step 2230 of method 2200. This isuseful for determining whether the DQ tape is suspect itself, and, toverify such a conclusion, the gold tape determined at step 2066 ofinitialization method 2000 is selected from the tape pool (DQ tape poolmay include this gold tape) or from the library.

It should be noted at this time that the drives and tapes identified asgold and/or DQ are available for ongoing data storage and use in thecustomer's tape library. These media and drives are only used as neededby the MDV module. In other words, the use of the term “pool” does notmean that these components are set aside or dedicated for use only bythe STA application and its MDV module. In this way, additional drives(or media) are not required in the library for performing MDV, and thecustomer's own data is used in the testing processes (e.g., to determineRQI values and the like).

In the method 2300, the suspected gold drive may optionally be cleanedat 2320. Then, at 2340, a statistical tool is run while the same DQ tapefrom the pool and the gold tape are each inserted into the gold drive.At 2350, if both tapes pass at 2340, the cleaning at 2320 is assumed tohave been effective such that the gold drive may again be used tovalidate tape (e.g., to perform method 2100 of FIG. 21). The failedtarget tape may be retested with the cleaned gold drive or may beidentified as dispositional based upon its prior failure with the golddrive.

However, several actions may be taken as part of process 2300 when thetapes fail in the cleaned gold drive in step 2340. At 2360, the method2300 may include determining that the DQ tape passed but the gold tapefailed. If this is the case, the initialization process 2000 of FIG. 20may be performed again because confidence is lost in the gold tape suchthat it is now suspect and a new gold drive and gold tape are needed forperforming MDV. This should rarely if ever occur.

At 2364, the method 2300 includes determining that both tapes failed thetesting at 2340. If this occurs, it is likely that the gold drive is badbecause with a sample of four tests the drive has failed with threetapes (again, this should be rare). At 2364, a new gold drive isidentified (or another initialized at 2060 of initialization method 2000of FIG. 20) and used to re-test the failed target tape. The prior goldtape is dispositioned (e.g., removed from the library or scheduled formaintenance).

At 2368, the method 2300 includes determining that the DQ tape failswith this gold drive but the gold tape passes. In this case, the DQ tapeis likely bad or degraded since the gold drive still performs well withthe gold tape. The DQ tape is marked or identified for properdisposition as bad/degraded (e.g., replaced in the library and markedfor no further use by the customer).

As a review, the initialization procedure identifies a gold drive(s), agold tape, and a pool of qualified tapes (DQ tapes). Initialization mayinclude: (a) requesting a set of tapes with a minimum of two wrapswritten as copy of customer data; (b) qualifying using a statisticaltool in a drive test; (c) qualifying one or more drives as gold from apool of customer selected drives (e.g., drives with all 64 datachannels); (d) qualifying a gold tape as one operating with a highestRQI from the set of tapes operating in the upper 25 percent of RQI; and(e) qualifying a set of DQ tapes as operating in the upper 25 percent ofRQI for later use (typically will not include the gold tape). Onceinitialization is complete, the MDV module and its functionality isready for the customer or STA user to use in managing operations oftheir tape storage library (or libraries of a data center).

MDV use may include running a statistical tool (e.g., a volumestatistical tool) with target tape on a gold drive. If the test ispassed, the tape is validated. If a permanent error is identified or thetest indicated degradation (e.g., RQI less than about 25 percent), thegold drive is tested. This testing may include running a mediastatistical testing tool with a random DQ tape using the gold drive. Ifthe drive/tape pass, the target tape may be copied and returned to ascratch pool. Alternatively, the target tape may be copied with perm andthen the tape may be dispositioned. If the drive/tape fail (perm erroror degraded), the gold drive may be re-qualified or re-certified asgold.

Re-qualifying of the gold drive may include cleaning the gold drive andrunning a media statistical tool with the same DQ tape and then with agold tape in the cleaned gold drive. If the DQ and gold tape both passthis statistical analysis/test, the target tape may be copied andreturned to a scratch pool. Alternatively, the target tape may be copiedwith perm and dispositioned. If the DQ tape passes and the gold tapefails, the initialization procedure may be run again. If the DQ tapefails and the gold tape passes, the DQ tape may be dispositioned. Ifboth fail, the target tape may be re-tested on a new gold drive and theprior gold drive may be dispositioned.

Further, it should be noted that different RQI limits may be used tovalidate a customer tape versus validating a DQ tape. Also, the abovemethods describe cleaning a defined gold drive prior to performingre-qualifying of a tape, but it should be understood that cleaning maynot be performed prior to re-qualifying in some implementations of thepresently described methods.

We claim:
 1. A method of validating tape drives and media in a tapelibrary, comprising: with a computer running an analytics module,receiving a validation request for a tape in the tape library; with thetape loaded into a predefined gold drive in the tape library, performinga statistical analysis on the tape to determine an operating parameterfor the tape in the predefined gold drive; and with the analyticsmodule, validating the tape when the operating parameter is greater thana threshold limit defined for the operating parameter for media in thetape library, wherein the operating parameter is read quality index(RQI).
 2. The method of claim 1, wherein the threshold limit is an RQIof 25 percent.
 3. The method of claim 1, further comprising, when theoperating parameter is less than about the threshold limit, running aperformance test on a drive qualified tape from the library loaded intothe predefined gold drive and, when the drive qualified tape passes theperformance test, identifying the tape as having degraded performance.4. The method of claim 3, wherein the operating parameter is RQI and thedrive qualified tape has an RQI greater than about 50 percent.
 5. Themethod of claim 3, further comprising, when the drive qualified tapefails the performance test, re-qualifying the predefined gold drive bydetermining whether the drive qualified tape and a predefined gold tapefrom the tape library pass a performance test when loaded into thepredefined gold drive, wherein when both the drive qualified tape andthe predefined gold tape pass the performance test identifying the tapeas having degraded performance.
 6. The method of claim 5, wherein there-qualifying is performed after cleaning of the predefined gold drive.7. The method of claim 5, further comprising, when the drive qualifiedtape fails the performance test and the predefined gold tape passes theperformance test, identifying the tape as having degraded performance.8. The method of claim 5, wherein the operating parameter is RQI and thepredefined gold tape has an RQI greater than about 75 percent.
 9. Themethod of claim 8, wherein the predefined gold tape, the drive qualifiedtape, and the predefined gold drive are concurrently available for dataoperations in the tape library and for use by the analytics module. 10.A data storage system configured for validating media and drives,comprising: a tape library comprising a plurality of tape drives and aplurality of tapes for use in the tape drives; a server communicativelylinked to the tape library; and on the server, a storage tape analyticsapplication: comparing read margin measurements for a number of the tapedrives in the tape library and designating one of the number of the tapedrives with a higher one of the read margin measurements as a golddrive; and validating performance of one of the tapes in the tapelibrary by comparing a read margin measurement for the one of the tapeswhile loaded in the gold drive against a threshold read margin, andwherein the gold drive remains available for data storage operations inthe tape library during the validating.
 11. The system of claim 10,wherein, based on the validating, a number of the one or more tapes areidentified as having degraded performance relative to the operatingparameter.
 12. The system of claim 11, wherein, prior to identifying thenumber of the tapes as having degraded performance, the storage tapeanalytics application causes the gold drive to be tested against one ormore performance parameters with a drive qualified one of the tapes. 13.The system of claim 12, wherein, when the gold drive fails the testingby the storage tape analytics application, the storage tape analyticsapplication further causes the gold drive to load one of the tapesdesignated as a gold tape, causes a performance testing to be performedwith the gold tape in the gold drive, and causes the gold drive to bere-qualified as a gold drive when the gold tape passes the performancetesting and to be degraded from gold status when the gold tape fails theperformance testing.
 14. The system of claim 13, wherein the gold driveis cleaned prior to the loading of the gold tape, wherein theperformance testing is further performed with the drive qualified one ofthe tapes, and wherein the gold drive is only degraded from the goldstatus when both the gold tape and drive qualified one of the tapes failthe performance testing.
 15. A tape validation method, comprising: withan analytics module running on a computer, comparing read marginmeasurements for a number of drives in a tape library and designatingone of the number of drives with a higher one of the read marginmeasurement as a gold drive; and with the analytics module, validatingperformance of a tape in the tape library by comparing a read marginmeasurement for the tape while loaded in the gold drive against athreshold read margin, wherein the gold drive remains available for datastorage operations in the tape library during the tape validationmethod.
 16. The method of claim 15, wherein the gold drive has a readquality index greater than 75 percent and the validating performance ofthe tape requires that the read margin measurement exceeds 25 percent.17. The method of claim 15, further comprising qualifying a tape fromthe tape library as a gold tape based on read margin measurementsobtained with the number of drives used in the designating of the golddrive step and identifying a number of other tapes from the tape libraryas drive qualified tapes based on read margin measurements obtained withthe number of drives.
 18. The method of claim 17, further comprising,when the read margin measurement used in the performance validatingfails to satisfy the threshold read margin, performance testing the golddrive using one of the drive qualified tapes prior to degrading the tapeused in the performance validating.
 19. The method of claim 18, furthercomprising, when the gold drive fails the performance testing,re-qualifying the gold drive by cleaning the gold drive and repeatingthe performance testing with the one of the drive qualified tapes andusing the gold tape.
 20. The method of claim 19, further comprising,when the one of the drive qualified tapes fails the performance testingand the gold tape passes the performance testing, removing the one ofthe drive qualified tapes from the drive qualified tapes.
 21. A methodof validating tape drives and media in a tape library, comprising: witha computer running an analytics module, receiving a validation requestfor a tape in the tape library; with the tape loaded into a predefinedgold drive in the tape library, performing a statistical analysis on thetape to determine an operating parameter for the tape in the predefinedgold drive; with the analytics module, validating the tape when theoperating parameter is greater than a threshold limit defined for theoperating parameter for media in the tape library; when the operatingparameter is less than about the threshold limit, running a performancetest on a drive qualified tape from the library loaded into thepredefined gold drive; and when the drive qualified tape passes theperformance test, identifying the tape as having degraded performance,wherein the operating parameter is RQI and the drive qualified tape hasan RQI greater than about 50 percent.
 22. The method of claim 21,wherein the threshold limit is an RQI of 25 percent.
 23. The method ofclaim 21, further comprising, when the drive qualified tape fails theperformance test, re-qualifying the predefined gold drive by determiningwhether the drive qualified tape and a predefined gold tape from thetape library pass a performance test when loaded into the predefinedgold drive, wherein when both the drive qualified tape and thepredefined gold tape pass the performance test identifying the tape ashaving degraded performance.
 24. The method of claim 23, wherein there-qualifying is performed after cleaning of the predefined gold drive.25. The method of claim 23, further comprising, when the drive qualifiedtape fails the performance test and the predefined gold tape passes theperformance test, identifying the tape as having degraded performance.26. The method of claim 23, wherein the operating parameter is RQI andthe predefined gold tape has an RQI greater than about 75 percent. 27.The method of claim 26, wherein the predefined gold tape, the drivequalified tape, and the predefined gold drive are concurrently availablefor data operations in the tape library and for use by the analyticsmodule.